Paul Rosin - Academia.edu (original) (raw)
Papers by Paul Rosin
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Neural Computing and Applications, Sep 1, 1998
We present a new benchmark for testing algorithms that create canonical forms for use in non-rigi... more We present a new benchmark for testing algorithms that create canonical forms for use in non-rigid 3D shape retrieval. We have combined two existing datasets to create a varied collection of models for testing. Canonical forms attempt to factor out a shape's pose, giving a pose-neutral shape. This opens up the possibility of using methods originally designed for rigid retrieval for the task of non-rigid shape retrieval. We demonstrate the benchmark by using it to compare the performance of nine canonical form methods, using three different retrieval algorithms.
A nested image is a form of artistic expression in which one or more secondary figures are embedd... more A nested image is a form of artistic expression in which one or more secondary figures are embedded within a primary figure, perhaps recursively. Contours of the primary figure are used to contain a sec-ondary figure; the effect has a particularly interesting artistic effect if parts of the secondary figure have a corresponding shape to inner holes of the primary figure. Here, we present a system for creating such images. Our system detects the enclosed outer contour of the figure to be nested, and then finds a place in the outer figure to embed it, together with a suitable transformation for doing so, by optimizing an energy based on the distance between the contours. We also allow small changes of shape, which can help to match contours. Morphing is done iteratively, warping the corresponding contours of the secondary figure and the holes of the primary figure to appropriate positions. We show various nested images generated by our system.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, Jan 26, 2017
Image colorization aims to produce a natural looking color image from a given grayscale image, wh... more Image colorization aims to produce a natural looking color image from a given grayscale image, which remains a challenging problem. In this paper, we propose a novel examplebased image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target grayscale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from ...
ACM Transactions on Graphics, 2021
Recent facial image synthesis methods have been mainly based on conditional generative models. Sk... more Recent facial image synthesis methods have been mainly based on conditional generative models. Sketch-based conditions can effectively describe the geometry of faces, including the contours of facial components, hair structures, as well as salient edges (e.g., wrinkles) on face surfaces but lack effective control of appearance, which is influenced by color, material, lighting condition, etc. To have more control of generated results, one possible approach is to apply existing disentangling works to disentangle face images into geometry and appearance representations. However, existing disentangling methods are not optimized for human face editing, and cannot achieve fine control of facial details such as wrinkles. To address this issue, we propose DeepFaceEditing, a structured disentanglement framework specifically designed for face images to support face generation and editing with disentangled control of geometry and appearance. We adopt a local-to-global approach to incorporate t...
HHMM structure; pattern recognition; motion analysis. The objective of this paper is to automatic... more HHMM structure; pattern recognition; motion analysis. The objective of this paper is to automatically build a Hierarchical Hidden Markov Model (HHMM) (Fine et al., 1998) structure to detect semantic patterns from data with an unknown structure by exploring the natural hierarchical decomposition embedded in the data. The problem is important for effective motion data representation and analysis in a variety of applications: film and game making, military, entertainment, sport and medicine. We propose to represent the patterns of the data as an HHMM built utilising a two-stage learning algorithm. The novelty of our method is that it is the first fully automated approach to build an HHMM structure for motion data. Experimental results on different motion features (3D and angular pose coordinates, silhouettes extracted from the video sequence) demonstrate the approach is effective at automatically constructing efficient HHMM with a structure which naturally represents the underlying mot...
IET 4th European Conference on Visual Media Production (CVMP 2007), 2007
Pattern Recognition, 2011
IEEE Transactions on Pattern Analysis and Machine Intelligence - PAMI, 1997
IEE Proceedings - Vision, Image, and Signal Processing, 1995
Architecture and Mathematics from Antiquity to the Future, 2014
The present study demonstrates the complementarity of the two methodologies—analysis with modern ... more The present study demonstrates the complementarity of the two methodologies—analysis with modern digital tools, and classical simulation with ancient tools—in the case study of Roman amphitheatres. The geometrical analysis and the arithmetical analysis both converge to the same conclusion. Furthermore they corroborate the conclusions suggested by the numerical analysis with modern mathematics (i.e., the manipulation of computer science). Therefore, the coherence of the results coming from our different approaches allows us to assert that the geometrical pattern of Pompeii’s amphitheatre is a rare example of elliptic shape in architecture. Furthermore, its geometry and dimensions also show some of the finest evidence of direct application of the latest discoveries in mathematical knowledge and science in architectural design in classic antiquity.
Machine Vision and Applications
Semantic segmentation has been proposed as a tool to accelerate the processing of natural history... more Semantic segmentation has been proposed as a tool to accelerate the processing of natural history collection images. However, developing a flexible and resilient segmentation network requires an approach for adaptation which allows processing different datasets with minimal training and validation. This paper presents a cross-validation approach designed to determine whether a semantic segmentation network possesses the flexibility required for application across different collections and institutions. Consequently, the specific objectives of cross-validating the semantic segmentation network are to (a) evaluate the effectiveness of the network for segmenting image sets derived from collections different from the one in which the network was initially trained on; and (b) test the adaptability of the segmentation network for use in other types of collections. The resilience to data variations from different institutions and the portability of the network across different types of col...
The standard approach to image instance segmentation is to perform the object detection first, an... more The standard approach to image instance segmentation is to perform the object detection first, and then segment the object from the detection bounding-box. More recently, deep learning methods like Mask R-CNN perform them jointly. However, little research takes into account the uniqueness of the "human" category, which can be well defined by the pose skeleton. Moreover, the human pose skeleton can be used to better distinguish instances with heavy occlusion than using bounding-boxes. In this paper, we present a brand new pose-based instance segmentation framework for humans which separates instances based on human pose, rather than proposal region detection. We demonstrate that our pose-based framework can achieve better accuracy than the state-of-art detection-based approach on the human instance segmentation problem, and can moreover better handle occlusion. Furthermore, there are few public datasets containing many heavily occluded humans along with comprehensive annota...
The severity of sustained injury resulting from assault-related violence can be minimised by redu... more The severity of sustained injury resulting from assault-related violence can be minimised by reducing detection time. However, it has been shown that human operators perform poorly at detecting events found in video footage when presented with simultaneous feeds. We utilise computer vision techniques to develop an automated method of abnormal crowd detection that can aid a human operator in the detection of violent behaviour. We observed that behaviour in city centre environments often occur in crowded areas, resulting in individual actions being occluded by other crowd members. We propose a real-time descriptor that models crowd dynamics by encoding changes in crowd texture using temporal summaries of Grey Level Co-Occurrence Matrix (GLCM) features. We introduce a measure of inter-frame uniformity (IFU) and demonstrate that the appearance of violent behaviour changes in a less uniform manner when compared to other types of crowd behaviour. Our proposed method is computationally che...
This paper describes a simple image-based method that applies engraving stylisation to portraits ... more This paper describes a simple image-based method that applies engraving stylisation to portraits using ordered dithering. Face detection is used to estimate a rough proxy geometry of the head consisting of a cylinder, which is used to warp the dither matrix, causing the engraving lines to curve around the face for better stylisation. Finally, an application of the approach to colour engraving is demonstrated.
Infrared imaging theory is an important theoretical basis for the design of infrared imaging syst... more Infrared imaging theory is an important theoretical basis for the design of infrared imaging systems, but there is no research on infrared imaging theory for designing thermal microscope imaging systems. Therefore, we studied the performance evaluation and optimization theory of thermal microscope imaging systems. In this paper, we analyzed the difference in spectral radiant flux between thermal microscope imaging and telephoto thermal imaging. The expression of signal-to-noise ratio of the output image of the thermal microscope imaging systems was derived, based on the analysis of the characteristics of thermal microscope imaging. We studied the performance evaluation model of thermal microscope imaging systems based on the minimum resolvable temperature difference and the minimum detectable temperature difference. Simulation and analysis of different detectors (ideal photon detector and ideal thermal detector) were also carried out. Finally, based on the conclusion of theoretical ...
Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Proceedings. International Conference on Image Processing, 2002
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Neural Computing and Applications, Sep 1, 1998
We present a new benchmark for testing algorithms that create canonical forms for use in non-rigi... more We present a new benchmark for testing algorithms that create canonical forms for use in non-rigid 3D shape retrieval. We have combined two existing datasets to create a varied collection of models for testing. Canonical forms attempt to factor out a shape's pose, giving a pose-neutral shape. This opens up the possibility of using methods originally designed for rigid retrieval for the task of non-rigid shape retrieval. We demonstrate the benchmark by using it to compare the performance of nine canonical form methods, using three different retrieval algorithms.
A nested image is a form of artistic expression in which one or more secondary figures are embedd... more A nested image is a form of artistic expression in which one or more secondary figures are embedded within a primary figure, perhaps recursively. Contours of the primary figure are used to contain a sec-ondary figure; the effect has a particularly interesting artistic effect if parts of the secondary figure have a corresponding shape to inner holes of the primary figure. Here, we present a system for creating such images. Our system detects the enclosed outer contour of the figure to be nested, and then finds a place in the outer figure to embed it, together with a suitable transformation for doing so, by optimizing an energy based on the distance between the contours. We also allow small changes of shape, which can help to match contours. Morphing is done iteratively, warping the corresponding contours of the secondary figure and the holes of the primary figure to appropriate positions. We show various nested images generated by our system.
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society, Jan 26, 2017
Image colorization aims to produce a natural looking color image from a given grayscale image, wh... more Image colorization aims to produce a natural looking color image from a given grayscale image, which remains a challenging problem. In this paper, we propose a novel examplebased image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target grayscale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from ...
ACM Transactions on Graphics, 2021
Recent facial image synthesis methods have been mainly based on conditional generative models. Sk... more Recent facial image synthesis methods have been mainly based on conditional generative models. Sketch-based conditions can effectively describe the geometry of faces, including the contours of facial components, hair structures, as well as salient edges (e.g., wrinkles) on face surfaces but lack effective control of appearance, which is influenced by color, material, lighting condition, etc. To have more control of generated results, one possible approach is to apply existing disentangling works to disentangle face images into geometry and appearance representations. However, existing disentangling methods are not optimized for human face editing, and cannot achieve fine control of facial details such as wrinkles. To address this issue, we propose DeepFaceEditing, a structured disentanglement framework specifically designed for face images to support face generation and editing with disentangled control of geometry and appearance. We adopt a local-to-global approach to incorporate t...
HHMM structure; pattern recognition; motion analysis. The objective of this paper is to automatic... more HHMM structure; pattern recognition; motion analysis. The objective of this paper is to automatically build a Hierarchical Hidden Markov Model (HHMM) (Fine et al., 1998) structure to detect semantic patterns from data with an unknown structure by exploring the natural hierarchical decomposition embedded in the data. The problem is important for effective motion data representation and analysis in a variety of applications: film and game making, military, entertainment, sport and medicine. We propose to represent the patterns of the data as an HHMM built utilising a two-stage learning algorithm. The novelty of our method is that it is the first fully automated approach to build an HHMM structure for motion data. Experimental results on different motion features (3D and angular pose coordinates, silhouettes extracted from the video sequence) demonstrate the approach is effective at automatically constructing efficient HHMM with a structure which naturally represents the underlying mot...
IET 4th European Conference on Visual Media Production (CVMP 2007), 2007
Pattern Recognition, 2011
IEEE Transactions on Pattern Analysis and Machine Intelligence - PAMI, 1997
IEE Proceedings - Vision, Image, and Signal Processing, 1995
Architecture and Mathematics from Antiquity to the Future, 2014
The present study demonstrates the complementarity of the two methodologies—analysis with modern ... more The present study demonstrates the complementarity of the two methodologies—analysis with modern digital tools, and classical simulation with ancient tools—in the case study of Roman amphitheatres. The geometrical analysis and the arithmetical analysis both converge to the same conclusion. Furthermore they corroborate the conclusions suggested by the numerical analysis with modern mathematics (i.e., the manipulation of computer science). Therefore, the coherence of the results coming from our different approaches allows us to assert that the geometrical pattern of Pompeii’s amphitheatre is a rare example of elliptic shape in architecture. Furthermore, its geometry and dimensions also show some of the finest evidence of direct application of the latest discoveries in mathematical knowledge and science in architectural design in classic antiquity.
Machine Vision and Applications
Semantic segmentation has been proposed as a tool to accelerate the processing of natural history... more Semantic segmentation has been proposed as a tool to accelerate the processing of natural history collection images. However, developing a flexible and resilient segmentation network requires an approach for adaptation which allows processing different datasets with minimal training and validation. This paper presents a cross-validation approach designed to determine whether a semantic segmentation network possesses the flexibility required for application across different collections and institutions. Consequently, the specific objectives of cross-validating the semantic segmentation network are to (a) evaluate the effectiveness of the network for segmenting image sets derived from collections different from the one in which the network was initially trained on; and (b) test the adaptability of the segmentation network for use in other types of collections. The resilience to data variations from different institutions and the portability of the network across different types of col...
The standard approach to image instance segmentation is to perform the object detection first, an... more The standard approach to image instance segmentation is to perform the object detection first, and then segment the object from the detection bounding-box. More recently, deep learning methods like Mask R-CNN perform them jointly. However, little research takes into account the uniqueness of the "human" category, which can be well defined by the pose skeleton. Moreover, the human pose skeleton can be used to better distinguish instances with heavy occlusion than using bounding-boxes. In this paper, we present a brand new pose-based instance segmentation framework for humans which separates instances based on human pose, rather than proposal region detection. We demonstrate that our pose-based framework can achieve better accuracy than the state-of-art detection-based approach on the human instance segmentation problem, and can moreover better handle occlusion. Furthermore, there are few public datasets containing many heavily occluded humans along with comprehensive annota...
The severity of sustained injury resulting from assault-related violence can be minimised by redu... more The severity of sustained injury resulting from assault-related violence can be minimised by reducing detection time. However, it has been shown that human operators perform poorly at detecting events found in video footage when presented with simultaneous feeds. We utilise computer vision techniques to develop an automated method of abnormal crowd detection that can aid a human operator in the detection of violent behaviour. We observed that behaviour in city centre environments often occur in crowded areas, resulting in individual actions being occluded by other crowd members. We propose a real-time descriptor that models crowd dynamics by encoding changes in crowd texture using temporal summaries of Grey Level Co-Occurrence Matrix (GLCM) features. We introduce a measure of inter-frame uniformity (IFU) and demonstrate that the appearance of violent behaviour changes in a less uniform manner when compared to other types of crowd behaviour. Our proposed method is computationally che...
This paper describes a simple image-based method that applies engraving stylisation to portraits ... more This paper describes a simple image-based method that applies engraving stylisation to portraits using ordered dithering. Face detection is used to estimate a rough proxy geometry of the head consisting of a cylinder, which is used to warp the dither matrix, causing the engraving lines to curve around the face for better stylisation. Finally, an application of the approach to colour engraving is demonstrated.
Infrared imaging theory is an important theoretical basis for the design of infrared imaging syst... more Infrared imaging theory is an important theoretical basis for the design of infrared imaging systems, but there is no research on infrared imaging theory for designing thermal microscope imaging systems. Therefore, we studied the performance evaluation and optimization theory of thermal microscope imaging systems. In this paper, we analyzed the difference in spectral radiant flux between thermal microscope imaging and telephoto thermal imaging. The expression of signal-to-noise ratio of the output image of the thermal microscope imaging systems was derived, based on the analysis of the characteristics of thermal microscope imaging. We studied the performance evaluation model of thermal microscope imaging systems based on the minimum resolvable temperature difference and the minimum detectable temperature difference. Simulation and analysis of different detectors (ideal photon detector and ideal thermal detector) were also carried out. Finally, based on the conclusion of theoretical ...
Proceedings / CVPR, IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Proceedings. International Conference on Image Processing, 2002