Michael Langer | McGill University (original) (raw)

Papers by Michael Langer

IEEE transactions on visualization and computer graphics, Jan 15, 2018

Lossy texture compression is increasingly used to reduce GPU memory and bandwidth consumption. Ho... more Lossy texture compression is increasingly used to reduce GPU memory and bandwidth consumption. However, evaluating the quality of compressed textures is a difficult problem. Indeed using PSNR on texture images, like done in most applications, may not be a correct way to proceed. In particular, there is evidence that masking effects apply when the texture image is mapped on a surface and combined with other textures. These masking effects have to be taken into account when compressing a set of texture maps, in order to have a real understanding of the visual impact of the compression artifacts on the rendered images. We present the first psychophysical experiment investigating the perceptual impact of texture compression. We explore the influence of compression bit rate, lighting, and diffuse and normal map content on the impact of artifacts. The collected data reveal huge masking effects from normal map to diffuse map artifacts and vice versa, and reveal the weakness of PSNR for eva...

Journal of Perceptual Imaging

Both natural scene statistics and ground surfaces have been shown to play important roles in visu... more Both natural scene statistics and ground surfaces have been shown to play important roles in visual perception, in particular, in the perception of distance. Yet, there have been surprisingly few studies looking at the natural statistics of distances to the ground, and the studies that have been done used a loose definition of ground. Additionally, perception studies investigating the role of the ground surface typically use artificial scenes containing perfectly flat ground surfaces with relatively few non-ground objects present, whereas ground surfaces in natural scenes are typically non-planar and have a large number of non-ground objects occluding the ground. Our study investigates the distance statistics of many natural scenes across three datasets, with the goal of separately analyzing the ground surface and non-ground objects. We used a recent filtering method to partition LiDAR-acquired 3D point clouds into ground points and non-ground points. We then examined the way in which distance distributions depend on distance, viewing elevation angle, and simulated viewing height. We found, first, that the distance distribution of ground points shares some similarities with that of a perfectly flat plane, namely with a sharp peak at a near distance that depends on viewing height, but also some differences. Second, we also found that the distribution of non-ground points is flatter and did not vary with viewing height. Third, we found that the proportion of non-ground points increases with viewing elevation angle. Our findings provide further insight into the statistical information available for distance perception in natural scenes, and suggest that studies of distance perception should consider a broader range of ground surfaces and object distributions than what has been used in the past in order to better reflect the statistics of natural scenes.

Computer Vision — ECCV '94, 1994

There are three reasons for illumination to vary within a scene. First, a light source may be vis... more There are three reasons for illumination to vary within a scene. First, a light source may be visible from some surfaces but not from others. Second, because of linear perspective, the shape and size of a finite source may be different when viewed from different points in a scene. Third, the brightness of a source may be non-uniform. These variations are captured by a new computational model of spatially varying illumination. Two types of source are described: a distant hemispheric source such as the sky in which light converges onto a scene, and a proximal source such as a lamp in which fight diverges into a scene. Either type of source may have a non-uniform brightness function. We show how to render surfaces using this model, and how to compute shape from shading under it.

Journal of Vision, 2018

The strength of motion parallax as a cue for depth order has been studied mostly for large observ... more The strength of motion parallax as a cue for depth order has been studied mostly for large observer motion [1-3]. Here we examine small observer motions e.g. over a distance of less than one cm. We examine how well subjects can judge depth order from such small motions (or "microparallax"). We also consider the defocus blur cue. Previous studies of this cue have considered static images only, and have shown that this cue is unreliable [4-6]. We examined whether the cue would be more reliable when combined with microparallax.

Lecture Notes in Computer Science, 1992

Surfaces in a 3−D scene are illuminated directly by light sources and also indirectly by each oth... more Surfaces in a 3−D scene are illuminated directly by light sources and also indirectly by each other, via interreflections.

Proceedings of the ACM Symposium on Applied Perception, 2013

Journal of Vision, 2012

Goal of our study: Measure perceived local qualitative shape under various rendering conditions (... more Goal of our study: Measure perceived local qualitative shape under various rendering conditions (monocular cues, no occlusions). Method: Mark points on rendered surfaces. Observers judge if shape is convex ("bump") or concave ("dent"). Motivation: Classical depth-reversal ambiguity (e.g.hollow mask illusion) applies to specular reflections too: inverting the depth and lighting gives almost he same image intensities (except for a small perspective cue). Does motion + perspective resolve this ambiguity ? Stimuli: subset of Exp1 + depth inversions Results: Discussion: Performance in mirror condition is above chance. Which suggests different weights of perspective cue vs "priors" (for viewpoint & light from above) for different conditions.

ACM Transactions on Applied Perception, 2009

arXiv (Cornell University), Nov 20, 2021

We address a data augmentation problem for LiDAR. Given a LiDAR scan of a scene from some positio... more We address a data augmentation problem for LiDAR. Given a LiDAR scan of a scene from some position, how can one simulate new scans of that scene from different, secondary positions? The method defines criteria for selecting valid secondary positions, and then estimates which points from the original point cloud would be acquired by a scanner from these positions. We validate the method using synthetic scenes, and examine how the similarity of generated point clouds depends on scanner distance, occlusion, and angular resolution. We show that the method is more accurate at short distances, and that having a high scanner resolution for the original point clouds has a strong impact on the similarity of generated point clouds. We also demonstrate how the method can be applied to natural scene statistics: in particular, we apply our method to reposition the scanner horizontally and vertically, separately consider points belonging to the ground and to nonground objects, and describe the impact on the distributions of distances to these two classes of points.

18th International Conference on Pattern Recognition (ICPR'06), 2006

This paper presents a novel method for the removal of unwanted image intensity due to occluding o... more This paper presents a novel method for the removal of unwanted image intensity due to occluding objects far from the plane of focus. Such occlusions may arise in scenes with large depth discontinuities, and result in image regions where both the occluding and background objects contribute to pixel intensities. The contribution of the occluding object's radiance is modeled by reverse projection, and can be removed from this region by a simple operation on the pixel's intensity. Experimental results demonstrate our ability to accurately recover the background's appearance despite significant occlusion. As compared with processing based a linear model of occlusion, the results show lower error and a more accurate contrast.

2016 Fourth International Conference on 3D Vision (3DV), 2016

Depth from defocus (DFD) requires estimating the depth dependent defocus blur at every pixel. Sev... more Depth from defocus (DFD) requires estimating the depth dependent defocus blur at every pixel. Several approaches for accomplishing this have been proposed over the years. For a pair of images this is done by modeling the defocus relationship between the two differently defocused images and for single defocused images by relying on the the properties of the point spread function and the characteristics of the latent sharp image. We propose depth discriminative filters for DFD that can represent many of the widely used models such as the relative blur, Blur Equalization Technique, deconvolution based depth estimation, and subspace projection methods. We show that by optimizing the parameters of this general model we can obtain state-of-the-art result on synthetic and real defocused images with single or multiple defocused images with different apertures.

Journal of vision, Mar 1, 2018

In three-dimensional (3-D) cluttered scenes such as foliage, deeper surfaces often are more shado... more In three-dimensional (3-D) cluttered scenes such as foliage, deeper surfaces often are more shadowed and hence darker, and so depth and luminance often have negative covariance. We examined whether the sign of depth-luminance covariance plays a role in depth perception in 3-D clutter. We compared scenes rendered with negative and positive depth-luminance covariance where positive covariance means that deeper surfaces are brighter and negative covariance means deeper surfaces are darker. For each scene, the sign of the depth-luminance covariance was given by occlusion cues. We tested whether subjects could use this sign information to judge the depth order of two target surfaces embedded in 3-D clutter. The clutter consisted of distractor surfaces that were randomly distributed in a 3-D volume. We tested three independent variables: the sign of the depth-luminance covariance, the colors of the targets and distractors, and the background luminance. An analysis of variance showed two m...

i-Perception

We perform two psychophysics experiments to investigate a viewer's ability to detect defocus ... more We perform two psychophysics experiments to investigate a viewer's ability to detect defocus in video; in particular, the defocus that arises in video during motion in depth when the camera does not maintain sharp focus throughout the motion. The first experiment demonstrates that blur sensitivity during viewing is affected by the speed at which the target moves towards the camera. The second experiment measures a viewer's ability to notice momentary defocus and shows that the threshold of blur detection in arc minutes decreases significantly as the duration of the blur increases. Our results suggest that it is important to have good control of focus while recording video and that momentary defocus should be kept as short as possible so it goes unnoticed.

Proceedings of the Workshop on Physics-Based Modeling in Computer Vision, 1995

Models of light sources and illumination are fun damental in physics-based vision. Light sources... more Models of light sources and illumination are fun damental in physics-based vision. Light sources have traditionally been modelled as objects that emit light, while illumination has been modelled as a radiance function defined over free space. The difficulty with traditional light source models is that, while a diverse collection of models exists, each is so specific that relationships between them, and between the algorithms based on them, are unclear. At the other extreme, models of spatial illumination have been so general that they have not provided sufficient constraint for vision. We seek to unify these two extremes by de veloping a ray-based computational model of light sources and illumination. sources and illumination. The model articulates strong constraints on the geometry and radiance of light rays in a scene, and expresses the relationship between free space, sources, and illumination. Appli cations of this model to problems in computer vision are discussed.

2015 International Conference on 3D Vision, 2015

Pictures taken with finite aperture lenses typically have out-of-focus regions. While such defocu... more Pictures taken with finite aperture lenses typically have out-of-focus regions. While such defocus blur is useful for creating photographic effects, it can also be used for depth estimation. In this paper, we look at different camera settings for Depth from Defocus (DFD), the conditions under which depth can be estimated unambiguously for those settings and optimality of different settings in terms of lower bound of error variance. We present results for general camera settings, as well as two of the most widely used camera settings namely, variable aperture and variable focus. We show that for variable focus, the range of depth needs to be larger than twice the focal length to unambiguously estimate depth. We analytically derive the optimal aperture ratio, and also show that there is no single optimal parameter for variable focus. Furthermore we show how to choose focus in order to minimize error variance in a particular region of the scene.

Lecture Notes in Computer Science

This paper presents a novel, automated method to remove partial occlusion from a single image. In... more This paper presents a novel, automated method to remove partial occlusion from a single image. In particular, we are concerned with occlusions resulting from objects that fall on or near the lens during exposure. For each such foreground object, we segment the completely occluded region using a geometric flow. We then look outward from the region of complete occlusion at the segmentation boundary to estimate the width of the partially occluded region. Once the area of complete occlusion and width of the partially occluded region are known, the contribution of the foreground object can be removed. We present experimental results which demonstrate the ability of this method to remove partial occlusion with minimal user interaction. The result is an image with improved visibility in partially occluded regions, which may convey important information or simply improve the image's aesthetics.