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1966 ieee computer society conference on computer vision and pattern recognition

作者： Lu, JP Little, J UNIV BRITISH COLUMBIA DEPT COMP SCILAB COMPUTAT INTELLIGENCEVANCOUVERBC V6T 1Z4CANADA

ISBN: (纸本)0818672587

In this paper we present a novel approach to surface recovery from an image sequence of a rotating object. In this approach, the object is illuminated under a collinear light source (where the light source lies on or near the optical axis) and rotated on a controlled turntable. A wire-frame of 3D curves on the object surface is extracted by using shading and occluding contours in the image sequence. Then the whole object surface is recovered by interpolating the surface between curves on the wire-frame. The interpolation can be done by using geometric or photometric constraints. The photometric method uses shading information and is more powerful than geometric methods. The experimental results on real image sequence of matte and specular surfaces show that the technique is feasible and promising.

关键词： computer vision

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Gauging relational consistency and correcting structural errors

Gauging relational consistency and correcting structural err...

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1966 ieee computer society conference on computer vision and pattern recognition

作者： Wilson, RC Hancock, ER UNIV YORK DEPT COMP SCIYORK YO1 5DDN YORKSHIREENGLAND

ISBN: (纸本)0818672587

The aim of this paper is to provide a comparative evaluation of a number of contrasting approaches to relational matching. Unique to this study is the way in which we show how a diverse family of algorithms relate to one-another using a common Bayesian framework. Broadly speaking there are two main aspects to this study. Firstly we focus on the issue of how relational inexactness may be quantified. We illustrate that several popular relational distance measures can be recovered as specific limiting cases of the same Bayesian consistency measure. The second aspect of our comparison concerns the way in which structural inexactness is controlled. We investigate three different realisations of the matching process which draw on contrasting control models. The main conclusion of our study is that the active process of graph-editing outperforms the alternatives in terms of its ability to effectively control a large population of contaminating clutter.

关键词： Object recognition

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Using bilinear models for view-invariant action and identity recognition

Using bilinear models for view-invariant action and identity...

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2006 ieee computer society conference on computer vision and pattern recognition, cvpr 2006

作者： Cuzzolin, Fabio UCLA Vision Lab. University of California at Los Angeles Boelter Hall 90025 Los Angeles CA

ISBN: (纸本)0769525970

Human identification from gait is a challenging task in realistic surveillance scenarios in which people walking along arbitrary directions are imaged by a single camera. In this paper, motivated by the view-invariance issue in the human ID from gait problem, we address the general problem of classifying the "content" of human motions of unknown "style". Given a dataset of sequences in which different people walking normally are seen from several well-separated views, we propose a three-layer scheme based on bilinear models, in which image sequences are mapped to observation vectors of fixed dimension using Markov modeling. We test our approach on the CMU Mobo database, showing how bilinear separation outperforms other approaches, opening the way to view- and action-invariant identity recognition, as well as subject- and view-invariant action recognition. © 2006 ieee.

关键词： Gesture recognition

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ABAW: Valence-Arousal Estimation, Expression recognition, Action Unit Detection & Multi-Task Learning Challenges

ABAW: Valence-Arousal Estimation, Expression Recognition, Ac...

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ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Kollias, Dimitrios Queen Mary Univ London London England

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

This paper describes the third Affective Behavior Analysis in-the-wild (ABAW) Competition, held in conjunction with ieee International conference on computer vision and pattern recognition (cvpr), 2022. The 3rd ABAW Competition is a continuation of the Competitions held at ICCV 2021, ieee FG 2020 and ieee cvpr 2017 conferences, and aims at automatically analyzing affect. This year the Competition encompasses four Challenges: i) uni-task Valence-Arousal Estimation, ii) uni-task Expression Classification, iii) uni-task Action Unit Detection, and iv) MultiTask-Learning. All the Challenges are based on a common benchmark database, Aff-Wild2, which is a large scale in-the-wild database and the first one to be annotated in terms of valence-arousal, expressions and action units. In this paper, we present the four Challenges, with the utilized Competition corpora, we outline the evaluation metrics and present both the baseline systems and the top performing teams' per Challenge. Finally we illustrate the obtained results of the baseline systems and of all participating teams.

关键词： Measurement computer vision Databases conferences Estimation Benchmark testing Multitasking

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Face recognition using 3-D models: Pose and illumination

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PROCEEDINGS OF THE ieee 2006年第11期94卷 1977-1999页

作者： Romdhani, Sami Ho, Jeffrey Vetter, Thomas Kriegman, David J. Univ Basel Dept Comp Sci CH-4056 Basel Switzerland Univ Florida Dept Comp & Informat Sci & Engn Gainesville FL 32611 USA Univ Calif San Diego Dept Comp Sci La Jolla CA 92093 USA

Unconstrained illumination and pose variation lead to significant variation in the photographs of faces and constitute a major hurdle preventing the widespread use of face recognition systems. The challenge is to generalize from a limited number of images of an individual to a broad range of conditions. Recently, advances in modeling the effects of illumination and pose have been accomplished using three-dimensional (3-D) shape information coupled with reflectance models. Notable developments in understanding the effects of illumination include the nonexistence of illumination invariants, a characterization of the set of images of objects in fixed pose under variable illumination (the illumination cone), and the introduction of spherical harmonics and low-dimensional linear subspaces for modeling illumination. To generalize to novel conditions, either multiple images must be available to reconstruct 3-D shape or, if only a single image is accessible, prior information about the 3-D shape and appearance of faces in general must be used. The 3-D Morphable Model was introduced as a generative model to predict the appearances of an individual while using a statistical prior on shape and texture allowing its parameters to be estimated from single image. Based on these new understandings, face recognition algorithms have been developed to address the joint challenges of pose and lighting. in this paper, we review these developments and provide a brief survey of the resulting face recognition algorithms and their performance.

关键词： biometrics computer vision face image analysis face recognition illumination invariant inverse rendering pose invariant

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Invariant histograms and deformable template matching for SAR target recognition

Invariant histograms and deformable template matching for SA...

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1966 ieee computer society conference on computer vision and pattern recognition

作者： Ikeuchi, K Shakunaga, T Wheeler, MD Yamazaki, T CARNEGIE MELLON UNIV SCH COMP SCIPITTSBURGHPA 15213

ISBN: (纸本)0818672587

Recognizing a target in synthetic-aperture radar (SAR) images is an important, yet challenging, application of the model-based vision technique. This paper describes a model-based SAR recognition system based on invariant histograms and deformable template matching techniques. An invariant histogram is a histogram of invariant values defined by geometric features such as points and lines in SAR images. Although a few invariants are sufficient to recognize a target, we use a histogram of all invariant values given by all possible target feature pairs. This redundant histogram enables robust recognition under severe occlusions typical in SAR recognition scenarios. Multi-step deformable template matching examines the existence of an object by superimposing templates over potential energy field generated from images or primitive features. It determines the template configuration which has the minimum deformation and the best alignment of the template with features. The deformability of the template absorbs the instability of SAR features. We have implemented the system and evaluated the system performance using hybrid SAR images, generated from synthesized model signatures and real SAR background signatures.

关键词： pattern recognition systems

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Training support vector machines: an application to face detection

Training support vector machines: an application to face det...

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1997 ieee computer society conference on computer vision and pattern recognition (cvpr 97)

作者： Osuna, E Freund, R Girosi, F Massachusetts Inst of Technology Cambridge United States

ISBN: (纸本)0780342364

We investigate the application of Support Vector Machines (SVMs) in computet vision. SVM is a learning technique developed by V. Vapnik and his team (AT&T Bell Labs.) that can be seen as a new method for training polynomial, neural network, or Radical Basis Functions classifiers. The decision surfaces are found by solving a linearly constrained quadratic programming problem. This optimization problem is challenging because the quadratic form is completely dense and the memory requirements grow with the square of the number of data points. We present a decomposition algorithm that guarantees global optimality, and can be used to train SVM's over very large data sets. The main idea behind the decomposition is the iterative solution of sub-problems and the evaluation of optimality conditions which are used both to generate improved iterative values, and also establish the stopping criteria for the algorithm. We present experimental results of our implementation of SVM, and demonstrate the feasibility of our approach on a face detection problem that involves a data set of 50,000 data points.

关键词： computer vision

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Region-tree based stereo using dynamic programming optimization

Region-tree based stereo using dynamic programming optimizat...

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2006 ieee computer society conference on computer vision and pattern recognition, cvpr 2006

作者： Lei, Cheng Selzer, Jason Yang, Yee-Hong IEEE Department of Computing Science University of Alberta

ISBN: (纸本)0769525970

In this paper, we present a novel stereo algorithm that combines the strengths of region-based stereo and dynamic programming on a tree approaches. Instead of formulating an image as individual scan-lines or as a pixel tree, a new region tree structure, which is built as a minimum spanning tree on the adjacency-graph of an over-segmented image, is used for the global dynamic programming optimization. The resulting disparity maps do not contain any streaking problem as is common in scanline-based algorithms because of the tree structure. The performance evaluation using the Middlebury benchmark datasets shows that the performance of our algorithm is comparable in accuracy and efficiency with top ranking algorithms. © 2006 ieee.

关键词： Stereo vision

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Controlled camera motions for scene reconstruction and exploration

Controlled camera motions for scene reconstruction and explo...

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1966 ieee computer society conference on computer vision and pattern recognition

作者： Marchand, E Chaumette, F UNIV RENNES 1 IRISAINRIA RENNESF-35042 RENNESFRANCE

ISBN: (纸本)0818672587

This paper deals with the 3D structure estimation and exploration of a scene using active vision. Our method is based on the structure from controlled motion approach which consists in constraining the camera motion in order to obtain a precise and robust estimation of the 3D structure of a geometrical primitive. Since this approach involves to gaze on the considered primitive, we present a method for connecting up many estimations in order to recover the complete spatial structure of scenes composed of cylinders and segments. We have developed perceptual strategies able to perform a succession of robust estimations without any assumption on the number and on the localization of the different objects. Furthermore, the proposed strategy ensures the completeness of the reconstruction. An exploration process centered on current visual features and on the structure of the previously studied primitives is presented. This leads to a gaze planning strategy that mainly uses a representation of known and unknown areas as a basis for selecting viewpoints. Finally, experiments carried out on a robotic cell have proved the validity of our approach.

关键词： computer vision

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Spatial weighting for bag-of-features

Spatial weighting for bag-of-features

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2006 ieee computer society conference on computer vision and pattern recognition, cvpr 2006

作者： Marszalek, Marcin Schmid, Cordelia INRIA Rhône-Alpes LEAR - GRAVIR 665 av de l'Europe 38330 Montbonnot France

ISBN: (纸本)0769525970

This paper presents an extension to category classification with bag-of-features, which represents an image as an orderless distribution of features. We propose a method to exploit spatial relations between features by utilizing object boundaries provided during supervised training. We boost the weights of features that agree on the position and shape of the object and suppress the weights of background features, hence the name of our method - "spatial weighting". The proposed representation is thus richer and more robust to background clutter. Experimental results show that our approach improves the results of one of the best current image classification techniques. Furthermore, we propose to apply the spatial model to object localization. Initial results are promising. © 2006 ieee.

关键词： pattern recognition systems

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