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Eye gaze tracking under natural head movements

Eye gaze tracking under natural head movements

引用

conference on computer vision and pattern recognition (cvpr)

作者： Zhiwei Zhu Qiang Ji Department of ECSE Rensselaer Polytechnic Institute Troy NY USA

ISBN: (纸本)0769523722

Most available remote eye gaze trackers based on pupil center corneal reflection (PCCR) technique have two characteristics that prevent them from being widely used as an important computer input device for human computer interaction. First, they must often be calibrated repeatedly for each individual; second, they have low tolerance for head movements and require the user to hold the head uncomfortably still. In this paper, we propose a solution for the classical PCCR technique that simplify the calibration procedure and allow free head movements. The core of our method is to analytically obtain a head mapping function to compensate head movement. Specifically, the head mapping function allows to automatically map the eye movement measurement under an arbitrary head position to a reference head position so that the gaze can be estimated from the mapped eye measurement with respect to the reference head position. Furthermore, our method minimizes the calibration procedure to only one time for each individual. Our proposed method significantly improves the usability of the eye gaze tracking technology, which is a major step for eye tracker to be accepted as a natural computer input device.

关键词： Tracking Head Calibration computer vision Human computer interaction Position measurement Cameras Reflection Motion measurement Usability

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Interactive shape from shading

Interactive shape from shading

引用

conference on computer vision and pattern recognition (cvpr)

作者： Gang Zeng Y. Matsushita Long Quan Heung-Yeung Shum Hong Kong University of Science and Technology Kowloon Hong Kong China Microsoft Research Asia Beijing Sigma Center Beijing China

Shape from shading (SfS) has always been difficult for real applications due to its intrinsic ill-posedness. In this paper, we propose an interactive SfS method which efficiently uses human knowledge in order to resolve ambiguity. We propose a global solution of continuous surfaces with a few constraints of surface normals that are interactively imposed to regularize the problem. A surface is divided into local patches, and each local solution is estimated with a fast marching SfS. It is shown that the boundaries of local solutions constitute a weighted Voronoi diagram, which allows for the formation of a global solution from the local ones. Finally, we optimize this global estimation by minimizing an energy functional based on shading and smoothness priors. Reconstruction results from both synthetic and real images demonstrate the usability of the new approach for various modeling applications.

关键词： Shape Humans Image reconstruction computer vision Surface reconstruction Asia Layout Usability Application software Optical reflection

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Statistical Learning of Visual Feature Hierarchies

Statistical Learning of Visual Feature Hierarchies

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： F. Scalzo J.H. Piater University of Liège Liege Belgium

We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method combines these primitives into high-level abstractions. Our appearance-based learning method uses local statistical analysis between features and Expectation- Maximization (EM) to identify and code spatial correlations. Spatial correlation is asserted when two features tend to occur at the same relative position of each other. This learning scheme results in a graphical model that allows a probabilistic representation of a flexible visual feature hierarchy. For feature detection, evidence is propagated using Nonparametric Belief Propagation (NBP), a recent generalization of particle filtering. In experiments, the proposed approach demonstrates efficient learning and robust detection of object models in the presence of clutter and occlusion and under view point changes.

关键词： Statistical learning Graphical models computer vision Learning systems Belief propagation Application software Statistical analysis Filtering Robustness Object detection

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Single Camera Stereo for Mobile Robot Surveillance

Single Camera Stereo for Mobile Robot Surveillance

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： J. McBride M. Snorrason T. Goodsell R. Eaton M.R. Stevens Charles River Analytics 슠Inc. Cambridge MA USA

Mobile robot designers frequently look to computer vision to solve navigation, obstacle avoidance, and object detection problems such as those encountered in parking lot surveillance. Stereo reconstruction is a useful technique in this domain. The advantage of a single-camera stereo method versus a stereo rig is the flexibility to change the baseline distance to best match each scenario. This directly increases the robustness of the stereo algorithm and increases the effective range of the system. The challenge comes from accurately rectifying the images into an ideal stereo pair. Structure from motion (SFM) can be used to compute the camera motion between the two images, but its accuracy is limited and small errors can cause rectified images to be misaligned. We present a single-camera stereo system that incorporates a Levenberg-Marquardt minimization of rectification parameters to bring the rectified images into alignment.

关键词： Robot vision systems Cameras Mobile robots Surveillance Stereo vision computer vision Navigation Object detection Stereo image processing Image reconstruction

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A slit scanning depth of route panorama from stationary blur

A slit scanning depth of route panorama from stationary blur

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conference on computer vision and pattern recognition (cvpr)

作者： Min Shi Jiang Yu Zheng Department of Computer Science Indiana University-Purdue University Indianapolis USA

ISBN: (纸本)0769523722

This work achieves an efficient acquisition of scenes and their depths along streets. During the movement of a vehicle, a slit in the camera frame is set properly to sample scenes continuously for a route panorama. This paper proposes a novel method of depth estimation by analyzing a new phenomenon named stationary blur in the route panorama. We find its relation with the depth and evaluate its degree at local and global levels. The depth estimation through filtering avoids feature matching and tracking that are error-prone in the scanning of real and complex street scenes. Our method provides reliable results but requires much less data than that of the structure from motion. This keeps the elegance of the route panorama in data representation, and is suitable for real time sensor development. Utilizing the completeness of the route panorama in the scene archiving, we can generate planar models of streets, which can be used in city visualization.

关键词： Layout Cameras Cities and towns Videos Vehicles Data visualization Image motion analysis pattern analysis computer science Matched filters

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Towards object-based heuristics

Towards object-based heuristics

引用

conference on computer vision and pattern recognition (cvpr)

作者： A.D. Gross Center for Research in Intelligent Systems Columbia University USA Department of Computer Science Queens College City University of New York USA

A survey and critique of previous work is given, and two object-based heuristics are developed. The structured nature of objects is the motivation for the nonaccidental alignment criterion; parallel lines within the object's bounding contour are related to the object-centered coordinate system. The regularity and symmetry inherent in many man-made objects is the motivation for the orthogonal basis constraint, an oblique set of coordinate axes in the image is presumed to be the projection of an orthogonal set of 3D coordinate axes in the scene. These heuristics are demonstrated on real and synthetic image contours.< >

关键词： Shape Layout Parametric statistics computer science Intelligent systems computer vision Geometry Labeling

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Repeated Measures GLMM Estimation of Subject-Related and False Positive Threshold Effects on Human Face Verification Performance

Repeated Measures GLMM Estimation of Subject-Related and Fal...

引用

ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： G.H. Givens J.R. Beveridge B.A. Draper P.J. Phillips Statistics Department Colorado State University USA Computer Science Department Colorado State University USA National Institute for Standards and Technology USA

Subject covariate data were collected on 1, 072 pairs of FERET images for analysis in a human face verification experiment. The subject data included information about facial hair, bangs, eyes, gender, and age. The verification experiment was replicated at seven different false alarm rates ranging from 1/10, 000 to 1/100. A generalized linear mixed model (GLMM) was fit to the binary outcomes indicating correct verification. Statistically significant main effects for bangs, eyes, gender, and age were found. The effect of the log false positive rate on verification success was found to interact significantly with bangs, gender, and age. These results have important implications for future evaluation of biometrics, and the GLMM methodology used here is shown to be effective and informative for this sort of data.

关键词： Humans Face recognition pattern recognition Performance analysis Eyes Statistics Virtual reality Statistical analysis computer science NIST

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A New Nonlinear Dimensionality Reduction Technique for Pose and Lighting Invariant Face recognition

A New Nonlinear Dimensionality Reduction Technique for Pose ...

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ieee computer society conference on computer vision and pattern recognition Workshops (cvprW)

作者： Ming-Jung Seow R.C. Tompkins V.K. Asari Computational Intelligence & Machine Vision Laboratory Old Dominion University Norfolk VA USA

One of the goals of biometrics research is to develop new techniques and/or algorithms for the automatic recognition of humans. In this paper, we propose the concept of a manifold of facial perception based on the observation that a perceived face in a set of similar face images-subjected to variations in pose, illumination and expression-defines a manifold in the high dimensional space. Such a manifold representation can be learned from images in a database of similar facial feature characteristics. This learned manifold can then be used as a basis for facial recognition. Development of a mathematical model for a nonlinear line attractor that represents a pattern manifold in the feature space is presented in this paper. The non-convex pattern manifolds in the feature space may be extremely complex and difficult to model. Therefore an adaptive divide and conquer modular approach which divides complex manifolds into smaller sub-manifolds in the feature space is also proposed for accurate modeling of the nonlinear line of attraction. A nonlinear dimensionality reduction technique using the learned matrices of the nonlinear line attractor network is then used to embed a set of related observations into a low-dimensional space that preserves the intrinsic dimensionality and metric structure of the data for fast and accurate face recognition. Results based on the proposed work from the first experiment of the FRGC version 2 database have shown promising performance in improving the accuracy in the face recognition.

关键词： Face recognition pattern recognition computer vision Principal component analysis Face detection Humans Computational intelligence Machine vision Laboratories Biometrics

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Model learning and recognition of nonrigid objects

Model learning and recognition of nonrigid objects

引用

conference on computer vision and pattern recognition (cvpr)

作者： J. Segen AT and T Bell Laboratories Holmdel NJ USA

A method of learning structural models of 2D shape from real data is described and demonstrated. These models can be used to classify nonrigid shapes, even if they are partially occluded, and to label their parts. The representation of a single shape is a layered graph whose vertices correspond to n-ary relations. A class of shapes is represented as a probability model whose outcome is a graph. The method is based on two types of learning: unsupervised learning used to discover relations, and supervised learning used to build class models. The class models are constructed incrementally, by matching and merging graphs representing shape instances. This process uses a fast graph-matching heuristic which seeks a simplest representation of a graph. An important feature is the self-generation of symbolic primitives by an unsupervised learning process. This feature makes it possible to apply the system to any set of shape data without adjustments, while other methods might require the user to provide a different set of primitives for each case.< >

关键词： Shape Biological system modeling Noise shaping Unsupervised learning Supervised learning Merging Humans Layout Character recognition

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Object recognition using invariant profiles

Object recognition using invariant profiles

引用

conference on computer vision and pattern recognition (cvpr)

作者： D. Slater G. Healey Computer Vision Laboratory Electrical and Computer Engineering University of California Irvine CA USA

We derive a sensitivity analysis for moment invariants of multidimensional distributions. These invariants have many uses in computational systems and have recently been used for illumination-invariant recognition in color images. In this context, the sensitivity analysis predicts the response of moment invariants to partial occlusion. Using the results of the sensitivity analysis, we develop a novel surface representation called the invariant profile which captures color distribution and spatial information while remaining invariant to the spectral content of the scene illumination. Unlike previous representations, the recognition of invariant profiles does not require illumination correction. We demonstrate the sensitivity analysis and the use of invariant profiles for recognition with a set of experiments on color images.

关键词： Object recognition Lighting Indexing Image databases Image recognition Image color analysis Sensitivity analysis Layout Spatial databases computer vision

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