Depth Map Research Papers - Academia.edu (original) (raw)

This paper presents an obstacle detection and avoidance of mobile robot using stereo camera for indoor environment. Block matching algorithm is solved the correspondence problem occurred in comparing stereo images (left and right sensors of the camera). The algorithm uses Sum of Absolute Differences (SAD). Left image works as a reference block to the right image and the output is disparity mapping or depth maps with the left coordinate system. A pair of camera or stereo vision baseline is based on horizontal configuration. The block matching technique is briefly described with the performance of its output. The curve fitting tool would determine the range of each obstacle detected in disparity mapping. The programming activities are using Matlab software starting from capturing images until navigation of mobile robot.

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- Computer Science, Robot Vision, Navigation, Mobile Robots

An investigation to localise facial landmarks from 3D images is presented, without using any assumption concerning facial pose. This paper introduces new surface descriptors, which are derived from either unstructured face data, or a radial basis function (RBF) model of the facial surface. Two new variants of feature descriptors are described, generally named as point - triplet descriptors because they require three vertices to be computed. The first is related to the classical depth map feature, which is referred to as weighted - interpolated depth map. The second variant of descriptors are derived from an implicit RBF model, they are referred to as surface RBF signature (SRS) features. Both variants of descriptors are able to encode surface information within a triangular region defined by a point - triplet into a surface signature, which could be useful not only for 3D face processing but also within a number of graph based retrieval applications. These descriptors are embedded into a system designed to localise the nose - tip and two inner - eye corners. Landmark localisation performance is reported by computing errors of estimated landmark locations against our respective ground --truth data from the Face Recognition Grand Challenge (FRGC) database.

- by Marcelo Romero
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- Radial Basis Function, System Design, 3-D Imaging, Face processing

: The leftmost and rightmost rendered images show synthetically relit textured surfaces based on albedo and surface depth acquired from a single view using diffuse-lit/flash-lit image pairs. The central (novel view) rendering was generated from a single image (shown in (a)) obtained from an online texture resource and matched to a similar exemplar for which we have recovered albedo and depth using the image-pair method.

- by Francho Melendez
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- Information Systems, Perception, Computational Photography, Depth Estimation

Fringe pattern analysis in coded structured light constitutes an active field of research. Techniques based on first projecting a sinusoidal pattern and then recovering the phase deviation permit the computation of the phase map and its corresponding depth map, leading to a dense acquisition of the measuring object. Among these techniques, the ones based on time-frequency analysis permit to extract the depth map from a single image, thus having potential applications measuring moving objects. The main techniques are Fourier Transform (FT), Windowed Fourier Transform (WFT) and Wavelet Transform (WT). This paper first analyzes the pros and cons of these three techniques, then a new algorithm for the automatic selection of the window size in WFT is proposed. This algorithm is compared to the traditional WT using adapted mother wavelet signals both with simulated and real objects, showing the performance results for quantitative and qualitative evaluations of the new method.

- by David Burton
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- Computer Vision, Qualitative evaluation, Wavelet Transform, Structured Light

This paper proposes a novel 3D scene interpretation approach for robots in mobile manipulation scenarios using a set of 3D point features (Fast Point Feature Histograms) and probabilistic graphical methods (Conditional Random Fields). Our system uses real time stereo with textured light to obtain dense depth maps in the robot's manipulators working space. For the purposes of manipulation, we want to interpret the planar supporting surfaces of the scene, recognize and segment the object classes into their primitive parts in 6 degrees of freedom (6DOF) so that the robot knows what it is attempting to use and where it may be handled. The scene interpretation algorithm uses a two-layer classification scheme: i) we estimate Fast Point Feature Histograms (FPFH) as local 3D point features to segment the objects of interest into geometric primitives; and ii) we learn and categorize object classes using a novel Global Fast Point Feature Histogram (GFPFH) scheme which uses the previously estimated primitives at each point. To show the validity of our approach, we analyze the proposed system for the problem of recognizing the object class of 20 objects in 500 table settings scenarios. Our algorithm identifies the planar surfaces, decomposes the scene and objects into geometric primitives with 98.27% accuracy and uses the geometric primitives to identify the object's class with an accuracy of 96.69%.

- by Andreas Holzbach
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- Image segmentation, Probability, Real Time, Depth Map

Falls are one of the major risks for seniors living alone at home. Computer vision systems, which do not require to wear sensors, offer a new and promising solution for fall detection. In this work, an occlusion robust method is presented based on two features: human centroid height relative to the ground and body velocity. Indeed, the first feature is an efficient solution to detect falls as the vast majority of falls ends on the ground or near the ground. However, this method can fail if the end of the fall is completely occluded behind furniture. Fortunately, these cases can be managed by using the 3D person velocity computed just before the occlusion.

- by Edouard Auvinet and +1
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- Computer Vision, Video Surveillance, Depth Map, D

This paper describes a fast technique for dressing virtual humans with different pieces of clothing. It exploits a mass-spring cloth model but applies a new velocity modification approach to overcome its super-elasticity. The algorithm for cloth-body collision detection and response is based on image-space interference tests, unlike most of the existing ones, which use objectspace checks. The modern workstations ’ graphics hardware is used not only to compute the depth maps of the body contours but also to interpolate the body normal vectors. As a result the approach is very fast and makes it possible to sew a garment around a virtual human body in about a second.

- by Bernhard Spanlang
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- Computer Science, Technology, Cloth Simulation, Collision detection

The problem considered in this paper involves the design of a vision-based autopilot for small and micro Unmanned Aerial Vehicles (UAVs). The proposed autopilot is based on an optic flow-based vision system for autonomous localization and scene mapping, and a nonlinear control system for flight control and guidance. This paper focusses on the development of a real-time 3D vision algorithm for estimating optic flow, aircraft self-motion and depth map, using a low-resolution onboard camera and a low-cost Inertial Measurement Unit (IMU). Our implementation is based on 3 Nested Kalman Filters (3NKF) and results in an efficient and robust estimation process. The vision and control algorithms have been implemented on a quadrotor UAV, and demonstrated in real-time flight tests. Experimental results show that the proposed vision-based autopilot enabled a small rotorcraft to achieve fully autonomous flight using information extracted from optic flow.

A peat layer is normally occurred in the Nile Delta at shallow depths, ranging from 5 to 15.5 meters with a maximum thickness of 3.5 meters. In this work, the area of southern Mansoura City was covered by a shallow geoelectrical survey aiming to delineate the peat layer to assist the engineers for future planning of the infra structures in the area. The survey included self potential (SP), induced polarization (IP) and time domain electromagnetic (TDEM) techniques.

- by Mohamed Metwaly
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- High Resolution, Depth Map, Self Potential, Induced Polarization

1 -A novel imaging technique is proposed for fully digital detection of phase and intensity of light. A fully integrated camera implementing the new technique was fabricated in a 0.35μm CMOS technology. When coupled to a modulated light source, the camera can be used to accurately and rapidly reconstruct a 3D scene by evaluating the time-offlight of the light reflected by a target. In passive mode, it allows building differential phase maps of reflection patterns for image enhancement purposes. Tests show the suitability of the technique and confirm phase accuracy predictions.

- by Edoardo Charbon
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- Image Processing, 3-D Imaging, Time of Flight, Image Enhancement

Photometric Stereo is a powerful image based 3d reconstruction technique that has recently been used to obtain very high quality reconstructions. However, in its classic form, Photometric Stereo suffers from two main limitations: Firstly, one needs to obtain images of the 3d scene under multiple different illuminations. As a result the 3d scene needs to remain static during illumination changes, which prohibits the reconstruction of deforming objects. Secondly, the images obtained must be from a single viewpoint. This leads to depth-map based 2.5 reconstructions, instead of full 3d surfaces. The aim of this chapter is to show how these limitations can be alleviated, leading to the derivation of two practical 3d acquisition systems: The first one, based on the powerful Coloured Light Photometric Stereo method can be used to reconstruct moving objects such as cloth or human faces. The second, permits the complete 3d reconstruction of challenging objects such as porcelain vases. In addition to algorithmic details, the chapter pays attention to practical issues such as setup calibration, detection and correction of self and cast shadows. We provide several evaluation experiments as well as reconstruction results.

- by Carlos Hernández
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- Deformable Objects, 3-D Reconstruction, Photometric Stereo, Depth Map

A three-dimensional (3-D) imager is presented, capable of computing the depth map as well as the intensity scale of a given scene. The heart of the system is a two-dimensional array of single photon avalanche diodes fabricated in standard CMOS technology. The diodes exhibit low-noise equivalent-power high-dynamic range, and superior linearity. The 3-D imager achieves submillimetric precision at a depth-of-field

- by Edoardo Charbon
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- Quantum Physics, High Dynamic Range, Optical physics, Three Dimensional

Combined 3-D interpretations of gravity and aeromagnetic data have been used in addition to continental and marine seismic profiles, well logs and geological cross-sections. The combination of gravity and magnetic data has improved the geometry and the density distribution in the 3-D calculated profiles. Results of the current work reveal possible crustal thickness and density distribution between the sedimentary cover and the upper mantle including the Moho discontinuity. The Moho depth map of the region, as obtained from the 3-D modeling exhibits various crustal thickness distributions. The type of crust changes gradually from continental to oceanic, from north to south. The zone of crustal thinning coincides mostly with zones of low-density, heated anomalous upper mantle beneath the rift floor (7 km). The eastern plateaus (the Red Sea hills) show by far the largest crustal thickness in the region (32 km).

- by Ahmed Saleh
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- Geology, Geophysics, Red Sea, Crustal Structure
- by Ryan Eustice
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- Light Scattering, Prior Knowledge, Oceans, Depth Map

Although three-dimensional (3D) displays enhance visual quality more than two-dimensional (2D) displays do, the depth information required for 3D displays is unavailable in the conventional 2D content. Therefore, converting 2D videos into 3D ones has become an important issue in emerging 3D applications. This work presents a novel algorithm that automatically converts 2D videos into 3D ones. The proposed algorithm utilizes the edge information to segment the image into object groups. A depth map is then assigned based on a hypothesized depth gradient model. Next, the depth map is block-based assigned by cooperating with a cross bilateral filter to generate visually comfortable depth maps efficiently and also diminish the block artifacts. A multiview video can be readily generated by using a depth image-based rendering method.

- by Jojo Tran
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- Image segmentation, Bilateral Filter, Three Dimensional, Depth Map

The European Plate has a 4.5 Gy long and complex tectonic history. This is reflected in the present-day large-scale crustal structures. A new digital Moho depth map is compiled from more than 250 data sets of individual seismic profiles, 3-D models obtained by body and surface waves, receiver function results and maps of seismic and/or gravity data compilations. We have

- by Timo Tiira and +6
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- Geology, Geophysics, Mediterranean Sea, Crustal Structure

We investigate 3-D basin structures and site resonance frequencies in the İzmit Bay area of Turkey by new geophysical surveys based on 239 single station microtremor and 405-point gravity measurements. A fundamental resonance frequency map of the İzmit Bay was produced from the main peak in the horizontal-to-vertical component spectral ratio (HVSR) of microtremors. The HVSR analysis of the microtremor data reveals single, double, broad peaked or no peak type HVSR curves varying in accordance with the surface geology and spatial extent of the three basins present in the İzmit Bay area. In the deepest sections of the İzmit, Gölcük and Derince basins of the İzmit Bay, the fundamental resonance frequencies are dominantly 0.24-0.30 Hz. These resonance frequencies should be taken into consideration along with higher mode frequencies to construct earthquake resistant structures in the İzmit Bay area. The 3-D gravimetric bedrock depth map of the İzmit basin shows that the basin has an asymmetric shape with its deepest section coinciding with the surface trace of the North Anatolian Fault. The northern shoulder of the basin has a gentle dip on the Kocaeli Peneplain side and the southern shoulder is much steeper, and it is bounded by the Samanlı Mountains. We derive a power-law relationship that correlates the fundamental site resonance frequencies with the sedimentary cover thickness obtained from the gravity and shear wave velocity data in the İzmit Bay. We use this relationship to estimate bedrock depths beneath Gölcük and Derince basins. Our estimation of maximum basin depths is 1400 m for the İzmit and is 800 m for the Gölcük and Derince basins. Finally, we have analysed a converted Sp phase from a local earthquake recording made at site CMP to calculate and verify the sediment thickness estimations obtained from our gravimetric and microtremor analyses. This calculation shows close agreement with that of the gravimetric and microtremor results. Our results show that the basins in the İzmit Bay area have a very thick sedimentary cover with very low shear velocities underlined by hard bedrock, forming a sharp impedance contrast. We anticipate that these results will be a key contribution to the quantitative assessment of seismic hazard for the İzmit Bay area before the occurrence of strong earthquakes in the Marmara region.

- by Ekrem Zor
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- Geology, Geophysics, Seismic Hazard, Geophysical Survey

Realistic and interactive telepresence has been a hot research topic in recent years. Enabling telepresence using depth-based new view rendering requires the compression and transmission of video as well as dynamic depth maps from multiple cameras. The telepresence application places additional requirements on the compressed representation of depth maps, such as preservation of depth discontinuities, low complexity decoding, and amenability to real-time rendering using graphics cards. We propose an adaptation of an existing triangular mesh generation method for depth representation that can be encoded efficiently. The mesh geometry is encoded using a binary tree structure where single bit enabled flags that mark the split of triangles and the depth values at the tree nodes are differentially coded. By matching the tree traversal to the mesh rendering order, both depth map decoding and triangle strip generation for efficient rendering are achieved simultaneously. The proposed scheme also naturally lends itself to coding segmented foreground layers and providing error resilience. At similar compression ratio, new view generation using the proposed method provided similar quality as depth compression using JPEG2000. However, the new mesh based depth map representation and compression method showed a significant improvement in rendering speed when compared to using separate compression and rendering processes.

- by Sriram Sethuraman
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- Cognitive Science, Real-time rendering, Real Time, Depth Map

In my thesis, I research the design and implementation of an online web-based application.

- by Minh Nguyen
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- Computer Vision, Image Reconstruction, Stereo Vision, Depth Map

The effects of varying the concentrations of cross-linker N, N′-methyelene-bis-acrylamide (BIS) from 2% to 4%, and 2-hydroxyethylacrylate (HEA) monomer from 2% to 4% at 5% gelatin on the dose response of BIS–HEA–gelatin (BHEAG) aqueous polymer gel dosimeters have been studied using magnetic resonance imaging (MRI) for relaxation rate (R2) of water proton. The dosimeters were irradiated with 60Co teletherapy γ-ray

- by Mohammad Omer
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- Geology, Chemistry, Radiation, Polymerization

I mage-based rendering (IBR) involves constructing an image from a new viewpoint, using several input images from different viewpoints. Our approach is to acquire or estimate the depth for each pixel of each input image. We then reconstruct the new view from the resulting collection of 3D points. When rendering images from photographs, acquiring and registering data is far from perfect. Accuracy can fluctuate, depending on the choice of geometry reconstruction technique. For example, even if we acquired depths with a laser scanner and registered them with their equivalent color images, we would still have problems, especially with occluded or very dark objects that don't reflect the laser beam. A rendering framework must be flexible enough to handle this kind of data. It must also be able to handle data extracted from several input images using far less accurate techniques-for example, stereo matching, which introduces a high level of uncertainty. We attempt to define this uncertainty and use it in our rendering framework. When synthesizing new images from real input images, IBR techniques often neglect to take advantage of all the knowledge gathered from computer vision techniques during depth recovery. (The "Related Work" sidebar discusses various other IBR approaches.) Our image-rendering approach involves three steps: depth extraction, uncertainty estimation, and rendering. That is, we first compute a depth map for every input image. Then we calculate the uncertainty information using the estimated depth maps as starting points. Finally, we perform the actual rendering, which renders the uncertainty estimated in the previous step as ellipsoidal Gaussian splats. Point-Based Computer Graphics Getting accurate depth information with computer vision's 3D estimation techniques is difficult. This image-based rendering algorithm provides quality views even when estimated depths are uncertain.

- by Nelson Max
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- Cognitive Science, Algorithms, Computer Graphics, Artificial Intelligence

We present PiCam (Pelican Imaging Camera-Array), an ultra-thin high performance monolithic camera array, that captures light fields and synthesizes high resolution images along with a range image (scene depth) through integrated parallax detection and superresolution. The camera is passive, supporting both stills and video, low light capable, and small enough to be included in the next generation of mobile devices including smartphones. Prior works [Rander et al. 1997; Yang et al. 2002; Zhang and Chen 2004; Tanida et al. 2001; Tanida et al. 2003; Duparré et al. 2004] in camera arrays have explored multiple facets of light field capture - from viewpoint synthesis, synthetic refocus, computing range images, high speed video, and micro-optical aspects of system miniaturization. However, none of these have addressed the modifications needed to achieve the strict form factor and image quality required to make array cameras practical for mobile devices. In our approach, we customize many ...

- by Priyam Chatterjee
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- Information Systems, Superresolution, Light field, Depth Map
- by arnav bhavsar
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- Visual Cues, Depth Map, Range Image, Range Image Segmentation

An efficient method that estimates the depth map of a 3D-scene using the motion information of the H.264-encoded 2D-video is presented. The motion information of the video-frames captured via a single camera is either directly used or modified to approximate the displacement (disparity) that exists between the right and left images when the scene is captured by stereoscopic cameras. Then, depth is estimated based on its inverse relation with disparity. The low-complexity of this method and its compatibility with future broadcasting networks allow its real-time implementation at the receiver; thus 3D-signal is constructed at no additional burden to the network. Performance evaluations show that this method outperforms the other existing H.264-based technique by up to 1.98 dB PSNR, providing more realistic depth information of the scene. Moreover subjective comparisons of the results, obtained by viewers watching the generated stereo video sequences on a 3D-display system, confirm the superiority of our method.

- by Rabab Ward
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- Depth Map, Electrical And Electronic Engineering

The main contribution of this paper is a novel stereo-based algorithm which serves as a tool to examine the viability of stereo vision solutions to the simultaneous localisation and mapping (SLAM) for large indoor environments. Using features extracted from the scale invariant feature transform (SIFT) and depth maps from a small vision system (SVS) stereo head, an extended Kalman filter (EKF) based SLAM algorithm, that allows the independent use of information relating to depth and bearing, is developed. By means of a map pruning strategy for managing the computational cost, it is demonstrated that statistically consistent location estimates can be generated for a small (6 m times 6 m) structured office environment, and in a robotics search and rescue arena of similar size. It is shown that in a larger office environment, the proposed algorithm generates location estimates which are topologically correct, but statistically inconsistent. A discussion on the possible reasons for the inconsistency is presented. The paper highlights that, despite recent advances, building accurate geometric maps of large environments with vision only sensing is still a challenging task

- by Jaime Valls Miro
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- Search and Rescue, Stereo Vision, Feature Extraction, Intelligent robots

We present a new image-based stereoscopic painterly algorithm that we use to automatically generate stereoscopic paintings. Our work is motivated by contemporary painters who have explored the aesthetic implications of painting stereo pairs of canvases. We base our method on two real images, acquired from spatially displaced cameras. We derive a depth map by utilizing computer vision depth-from-stereo techniques and use this information to plan and render stereo paintings. These paintings can be viewed stereoscopically, in which case the pictorial medium is perceptually extended by the viewer to better suggest the sense of distance.

- by Efstathios Stavrakis
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- Automatic code generation, Depth Map, Utility Computing

Visual processing is very important for robot navigation. It has been demonstrated that many complex operations, which deserve an intelligent behaviour, can be performed relying only on re exes to visual stimuli. In this framework the detection of corridors of free space along the robot trajectory is certainly a very important capability to safely navigate. Stereo vision and motion parallax can be used as cues to infer scene structure and determine free space areas. In this paper we propose a cooperative schema in which binocular disparity, computed on several stereo images over time, is combined with optical ow from the same sequence to obtain a relativedepth map of the scene. Both time-to-impact and depth scaled by the distance of the camera from the xation point in space are considered as good, relative measurements which are based on the viewer (but centered on the environment). Simple relations are de ned which combine disparity and optical ow for relative-depth estimates. In particular, some aspects of dynamic stereo vision are considered. Two experiments, performed on image sequences from real scenes, are presented.

- by Giulio Sandini
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- Computer Vision, Optical Flow, Navigation, Robot kinematics

: One-bounce diffuse global illumination rendered at 800×800 pixels for a scene with dynamic geometry (17 k faces) and dynamic lighting at 19.7 fps. Our method uses soft shadows from 30 area lights to efficiently compute the indirect... more

- by Zhao Dong
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- Image Processing, Real Time, Belief Propagation, Depth Map
- by Marc Pollefeys
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- Computer Vision, Structure from Motion, Video Streaming, Feature tracking

Three-dimensional shape recovery from one or multiple observations is a challenging problem of computer vision. In this paper, we present a new Focus Measure for the estimation of a depth map using image focus. This depth map can subsequently be used in techniques and algorithms leading to the recovery of a three-dimensional structure of the object, a requirement of a number of high level vision applications. The proposed Focus Measure has shown robustness in the presence of noise as compared to the earlier Focus Measures. This new Focus Measure is based on an optical transfer function implemented in the Fourier domain. The results of the proposed Focus Measure have shown drastic improvements in estimation of a depth map, with respect to the earlier Focus Measures, in the presence of various types of noise including Gaussian, Shot, and Speckle noises. The results of a range of Focus Measures are compared using root mean square error and correlation metric measures. ᭧

- by Tae-sun Choi
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- Computer Vision, Pattern Recognition, Root-Mean Square Error, Three Dimensional

In vision-based hand mouse, many existing algorithms use the RGB images which may provide useful information. However, for realtime purposes, RGB-image based methods may require fast and costly processors to handle high computational complexity. We propose a realtime hand mouse system using only the depth sensor of a Xbox-Kinect 1 . In our system, hand mouse is activated by hand shaking, and the algorithm tracks the hand to produce the motion trajectory of the mouse pointer. A mouse click is implemented by just folding and unfolding the index finger.

- by Changsoo Je
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- Kinect, Microsoft Kinect Applications, Depth Map

135 invariance. The fingerprints of these three models can easily and directly be geometrically deduced from the fingerprints of the one-dimensional models. The fingerprints should be viewed as cylinders over a base curve which is precisely the fingerprint of the corresponding one-dimensional edge model. In this way fingerprints of the two-dimensional models can be immediately visualized from their one-dimensional counterparts. We also demonstrate that the range of influence of one edge (upon another edge) located a distance d away begins at a scale of d/3.

- by Lingxiao Li
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- Mathematics, Computer Science, Theoretical Analysis, Depth Map

An efficient, physics-based remote bathymetry method for the littoral zone is described and illustrated with applications to QuickBird, Littoral Airborne Sensor: Hyperspectral (LASH), and Airborne Visible/Infrared Spectrometer (AVIRIS) spectral imagery. The method combines atmospheric correction, water reflectance spectral simulations, and a linear unmixing bathymetry algorithm that accounts for water surface reflections, thin clouds, and variable bottom brightness, and can incorporate blends of bottom materials. Results include depth maps, bottom color visualizations, and in favorable cases, approximate descriptions of the water composition. In addition, atmospheric correction was advanced through new capabilities added to the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and Moderate Resolution Transmittance (MODTRAN) codes, including characterization of the aerosol wavelength dependence and a discrete-ordinate-method radiative transfer scaling technique for rapid calculation of multiply scattered radiance.

- by Steven Adler-Golden
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- Cartography, Geophysics, Algorithms, Image Processing

Sinai Peninsula is considered as a unique region in the world due to its geographical location, tectonic and thermal activities. It is located geographically at the crossroads of Europe, Asia, and Africa constituting a triple junction point between the three continents. It is also characterized by thermal manifestations represented by several hot springs with varied temperatures (30–70 °C). Most of these hot springs are located along the shoreline of the Gulf of Suez.In this study, we aim to map the Curie depth isotherm surface for Sinai Peninsula based on the analysis of ground magnetic data. Spectral analysis technique will be used to estimate the boundaries (top and bottom) of the magnetized crust. The depths obtained for the bottom of magnetized crust are assumed to correspond to Curie point depths where the magnetic layer loss its magnetization.Results of this study indicate that the shallow Curie depths (~ 15–18 km) are located at the southern part of Sinai Peninsula and along the shoreline of the Gulf of Suez and depths increase (22–25 km) towards the central and north western portions of Sinai Peninsula. The whole average Curie depth point of Sinai Peninsula is about 20 km. Generally, the shallow depths to Curie isotherm indicate that Sinai Peninsula is a promising area for further geothermal exploration particularly near the eastern side of the Gulf of Suez.► This article addresses a very important issue related with geothermal exploration. ► The Curie depth surface is estimated from the analysis of magnetic data in Sinai Peninsula, Egypt. ► The most important result is that, once you have an area with high frequent earthquakes, the Curie depth will be shallow.

- by Essam Aboud
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- Geology, Geochemistry, Geophysics, Geothermal

The paper presents a novel algorithm for object space reconstruction from the planar (2D) recorded data set of a 3D-integral image. The integral imaging system is described and the associated point spread function is given. The space data extraction is formulated as an inverse problem, which proves ill-conditioned, and tackled by imposing additional conditions to the sought solution. An adaptive constrained 3D-reconstruction regularization algorithm based on the use of a sigmoid function is presented. A hierarchical multiresolution strategy which employes the adaptive constrained algorithm to obtain highly accurate intensity maps of the object space is described. The depth map of the object space is extracted from the intensity map using a weighted Durbin–Willshaw algorithm. Finally, illustrative simulation results are given.

- by Amar Aggoun
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- Inverse Problems, 3-D Reconstruction, Inverse Problem, Depth Map

A new vision-based obstacle avoidance technique for indoor navigation of Micro Aerial Vehicles (MAVs) is presented in this paper. The vehicle trajectory is modified according to the obstacles detected through the Depth Map of the surrounding environment, which is computed online using the Optical Flow provided by a single onboard omnidirectional camera. An existing closed-form solution for the absolute-scale velocity estimation based on visual correspondences and inertial measurements is generalized and here employed for the Depth Map estimation. Moreover, a dynamic region-of-interest for image features extraction and a self-limitation control for the navigation velocity are proposed to improve safety in view of the estimated vehicle velocity. The proposed solutions are validated by means of simulations.

- by Vincenzo Lippiello
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- Optical Flow, Velocity Estimation, Obstacle Avoidance, Depth Map

This paper considers techniques for capturing 3D information from image sequences for applications in film and TV production. The potential applications fall into two classes, one requiring 3D data that can be represented as a depth map from a single viewpoint, and the other requiring a full 3D model. Applications for both classes of data are briefly reviewed, and current work on 3D data capture in two EU-funded projects is described. The MetaVision project is considering depth map acquisition, and results based on a three-camera stereo system are presented. The development of a multi-camera system using widelyseparated cameras in a studio environment is being carried out as a part of the ORIGAMI project.

- by Oliver Grau
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- Animation, Production, TV, 3-D Imaging

The Curie point depth map of Western Anatolia was constituted from spectral analysis of the aeromagnetic data. The Curie point depth values from 53 overlapping blocks, 90 × 90 km in size, have been estimated from the band-pass filtered data. The slope of the longest wavelength part of the radially averaged log power spectrum divided by the radial frequency produced the depth to the centroid (z 0) for the deepest crustal block. The depth to the top (z t) was obtained by the slope of the second longest wavelength part of the spectrum. From these depths, the Curie point depth was then calculated by using z b =2z 0−z t . The Curie point depth estimates for Western Anatolia range between 8.2 and 19.9 km. A corresponding heat-flow map has been constructed from the Curie point depths and thermal conductivity measurements. The boundary between the areas of shallow and deep Curie point depth coincides with an active extensional system which is characterized by a complex cross-cutting horst-graben system. Deepening of Curie point depths (low heat flows) are observed at Hellenic trench axes. The shallow Curie point depths observed in the western part of the study area correspond with recent geological features such as the grabens of the Menderes Massif.

- by N. Orbay and +2
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- Geophysics, Thermal Conductivity, Spectrum, Depth Estimation
- by Berthold Horn
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- Computer Vision, Low Power, Analog VLSI, Chip

In the context of the study of brain morphogenesis, we present here a framework for surface-based group analysis using local cortical features in the neonate brain. We propose to detect and match local maxima from curvature and depth profiles of sulcal fundi. Such entities could have a key role to understand the variability of the brain morphology. We also describe a cortical localization tool dedicated to the developing brain. The proposed method is performed on a dataset of 25 preterm newborns and has detected consistent entities at the group level, both from cortical curvature and depth maps.

- by Denis Rivière
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- Stability Analysis, Surface topography, Structure Analysis, Surface Morphology
- by Bkp Horn
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- Biomedical Engineering, Image Processing, Visual perception, Machine Vision

Recent works in image editing are opening up new possibilities to manipulate and enhance input images. Within this context, we leverage well-known characteristics of human perception along with a simple depth approximation algorithm to generate non-photorealistic renditions that would be difficult to achieve with existing methods. Once a perceptually plausible depth map is obtained from the input image, we show

- by Jorge Farias Jimenez
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- Computer Science, Image Processing, Non-photorealistic rendering, Computers

- by Jorge Jimenez R
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- Computer Science, Image Processing, Non-photorealistic rendering, Computers

I would like to sincerely acknowledge my supervisor Professor John S. Zelek for all the guidance, kindness and support he has provided me throughout this study. I cannot imagine completing my thesis without his insightful supervision and continuous support. I would also like to express my appreciation to my thesis readers, Professor Paul Fieguth and Professor Otman Basir, for providing me with their valuable comments. In addition, I would like to thank the Defense Research and Development Canada (DRDC) for partially supporting this research.

- by John Zelek
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- Computer Vision, Visual perception, Stereopsis, Image segmentation
- by Maria Serna
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- Heuristics, Approximation Algorithms, Complexity, Reverse Engineering

Depth map is used for recovery of three-dimensional structure of the object which is required in many high level vision applications. In this paper, we present a new algorithm for the estimation of depth map for three-dimensional shape recovery. This algorithm is based on Fuzzy-Neural approach using shape from focus (SFF). A Fuzzy Inference System (FIS) is designed for the calculation of the depth map and an initial set of membership functions and fuzzy rules are proposed. Then Neural Network is used to train the FIS. The training is done using back propagation algorithm in combination with the least squares method. Hence, a new set of input membership functions are generated while discarding the initial ones. Lastly, the trained FIS is used to obtain final depth map. The results are compared with five other methods including the traditional SFF method and the Focused Image Surface SFF method (FISM). Six different types of objects are used for testing the proposed algorithm.

- by humaira nisar
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- Information Systems, Applied Mathematics, Fuzzy Logic, Back Propagation

- by Francho Melendez and +1
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- Information Systems, Perception, Computational Photography, Depth Estimation