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Model SelectionWithin a Bayesian Approach to Extraction of Walker Motion

Model SelectionWithin a Bayesian Approach to Extraction of W...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Ziheng Zhou R.I. Damper A. Prugel-Bennett Signals Images Systems (ISIS) Research Group School of Electronics and Computer Science University of Southampton Southampton UK

Extracting articulated motion of walking people in image sequences remains a challenge, particularly when we take into account the changes caused by carried objects or the severe motion occlusions by clothing (e.g., a long skirt, a trench coat, etc). In this paper, we propose a Bayesian framework capable of handling such uncertainties by exploiting our strong prior knowledge of how humans walk. In this work, the strong prior is built from a simple articulated model, which can be easily modified to cater for situations such as walkers wearing clothing that obscures the limbs. A model selection process is built into the framework to determine the body configuration of the walker in the given sequence automatically. The statistics of the parameters describing a basic walker are learned from data and the Bayesian framework then allows us to ‘bootstrap’ to accurate motion extraction on the images of walkers with extra body configurations. We demonstrate our approach on the data of walkers with rucksacks, skirts and trench coats. Results are quantified in terms of average pixel error between automatically extracted body points and corresponding points labelled by hand.

关键词： Bayesian methods Data mining Clothing Humans Biological system modeling Hidden Markov models Legged locomotion Image sequences Uncertainty Statistics

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Consistency of location and gradient judgments of visually-interpolated contours

Consistency of location and gradient judgments of visually-i...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： J.M. Fulvio M. Singh L.T. Maloney Psychology New York University New York NY USA Psychology & Cognitive Science Rutgers University-New Brunswick Piscataway NJ USA Psychology & Neural Science New York University New York NY USA

We report two experiments assessing how observers interpolate partly-occluded contours induced by pairs of line segments that disappeared behind an occluder. On each trial observers iteratively adjusted the location and orientation of a short line probe that could be moved vertically within the region of occlusion. They were instructed to set the line probe to be tangent to the occluded contour. The line probe could appear at one of six horizontal offsets and the inducer pairs on some trials were relatable (the inducers could be joined by a smooth curve without a point of inflection) and on other trials non-relatable. We interpreted the settings as estimates of the location and gradient (slope) of the contour in the region of occlusion. We tested whether the resulting visual estimates of location and gradient were consistent with any single smooth contour. When inducers were relatable, estimates of location and gradient were mutually consistent for all observers and could be modeled as polynomials of 5^th or lower degree. When the inducers were non-relatable, the consistency of location and gradient settings deteriorated, indicating that there can be no single smooth curve that accounts for observers’ judgments. We discuss the implication of these results for models of human visual interpolation.

关键词： Interpolation Psychology computer vision pattern recognition conferences Shape measurement Displays Turning Cognitive science Testing

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Liveness Detection for Fingerprint Scanners Based on the Statistics of Wavelet Signal Processing

Liveness Detection for Fingerprint Scanners Based on the Sta...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Bozhao Tan S. Schuckers Department of Electrical and Computer Engineering Clarkson University Potsdam NY USA

Fingerprint scanners can be spoofed by artificial fingers using moldable plastic, clay, Play-Doh, gelatin, silicone rubber materials, etc. Liveness detection is an anti-spoofing method which can detect physiological signs of life from fingerprints to ensure only live fingers can be captured for enrollment or authentication. In this paper, a new method based on the wavelet transform on the ridge signal extracted along the ridge mask is proposed which can detect the perspiration phenomenon using only a single image. Statistical features are extracted for multiresolution scales to discriminate between live and non-live fingers. Based on these features, we use a classification tree to generate the decision rules for the liveness classification. We test this method on the dataset which contains about 58 live, 80 spoof (50 made from Play-Doh and 30 made from gelatin), and 25 cadaver subjects for 3 different scanners. Also, we test this method on a second dataset which contains 33 live and 33 spoof (made from gelatin) subjects. The proposed liveness detection method is purely software based and application of this method can provide anti-spoofing protection for fingerprint scanners.

关键词： Fingerprint recognition Statistics Signal processing Fingers Classification tree analysis Testing Plastics Rubber Authentication Wavelet transforms

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The Tyzx DeepSea G2 vision System, ATaskable, Embedded Stereo Camera

The Tyzx DeepSea G2 Vision System, ATaskable, Embedded Stere...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： J.I. Woodfill G. Gordon D. Jurasek T. Brown R. Buck Tyzx Inc. Menlo Park CA USA

Our goal is to build vision systems suitable for deployment in devices that operate in demanding dynamic, variably lit, real-world environments. For such systems to be successful, not only must they perform their visual analysis well and robustly, but they must also be small, cheap and consume little power. Further, since volume deployments of such vision systems are still nascent, the systems must be taskable -- flexible enough to support many different uses. We have met our goal with the Tyzx DeepSea G2 Stereo vision System, an embedded stereo camera consisting of two CMOS imagers, a DeepSea II stereo ASIC, an FPGA, a DSP/Co-processor and a PowerPC running Linux, connected to the Ethernet. It is made practically taskable by the definition of a set of configurable visual primitives supported by specific hardware acceleration. These primitives include stereo correlation, color and depth background modeling, and 2D and 3D quantized representations or projections of the range data. We have defined a common programming interface in which the visual primitives are available both in traditional workstation environments, supported in software, and on the G2 with hardware acceleration. Single G2s are deployed in mobile platforms such as robots and automobiles, while networks of G2s are deployed in tracking systems in public and private sites around the world.

关键词： Machine vision Cameras Hardware Acceleration Vehicle dynamics Performance analysis Robustness Stereo vision CMOS image sensors Application specific integrated circuits

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Motion Segmentation by Spatiotemporal Smoothness Using 5D Tensor Voting

Motion Segmentation by Spatiotemporal Smoothness Using 5D Te...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Changki Min G. Medioni Integrated Media Systems Center University of Southern California Los Angeles CA USA

Our goal is to recover temporal trajectories of all pixels in a reference image for the given image sequence, and segment the image based on motion similarities. These trajectories can be visualized by observing the 3D (x, y, t) spatiotemporal volume. The mathematical formalism describing the evolution of pixels in time is that of fiber bundles, but it is difficult to implement directly. Instead, we express the problem in a higher dimensional 5D space, in which pixels with coherent apparent motion produce smooth 3D layers. The coordinates in this 5D space are (x, y, t, vx, vy). It is initially populated by peaks of correlation. We then enforce smoothness both in the spatial and temporal domains simultaneously, using the tensor voting framework. Unlike the previous 4D approach which uses only two frames, we fully take advantage of the temporal information through multiple images, and it significantly improves the motion analysis results. The approach is generic, in the sense that it does not make restrictive assumptions on the observed scene or on the camera motion. We present some results on real data sets, and they are very good on even challenging image sequences such as serious occlusion.

关键词： Motion segmentation computer vision Spatiotemporal phenomena Tensile stress Voting Image sequences Pixel Image segmentation Visualization Motion analysis

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Space-Sampling Method for 3D Cinemas

Space-Sampling Method for 3D Cinemas

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： T. Senoh T. Aoki H. Yasuda T. Kogure Research Center for Advanced Science & Technology University of Tokyo Tokyo Japan

A new approach to 3D Cinematography based on Space-Sampling method is presented. This method treats a projected 3D image space instead of a linear 3D space. It well matches with the visual perception and nicely reduces the data size needed for 3D scenes. It also matches with the 3D camera-shooting and the 3D displays requiring no eyewear. Space-Sampling method captures 3D natural scenes through a lens with transparent image-sensor layers. Hence, the 3D image space is directly sampled at a video-rate with single camera. Captured images are rendered on a transparent multi-layer display. Thus, a truly volumetric image is observed without eyeglasses. Combination rendering of these natural scenes with 3D computer-graphic (CG) objects creates a realistic Synthesized & Natural Hybrid scene at a reasonable cost. Depth from Focus technology and Depth-Fuse anti-aliasing technology were used to eliminate the blurred objects and to enhance the depth resolution, respectively.

关键词： Motion pictures Layout Rendering (computer graphics) Cinematography Visual perception Three dimensional displays Lenses Cameras computer displays Character generation

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Estimating Mixing Factors Simultaneously in Multilinear Tensor Decomposition for Robust Face recognition and Synthesis

Estimating Mixing Factors Simultaneously in Multilinear Tens...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Sung Won Park M. Savvides Electrical and Computer Engineering Department Carnegie Mellon University Pittsburgh PA USA

Facial images change appearance due to multiple factors such as poses, lighting variations, facial expressions, etc. Tensor approach, an extension of conventional matrix, is appropriate to analyze facial factors since tensors make it possible to construct multilinear models using a multiple factor structure. We use higher-order tensors to model multiple factors of facial variations, but this provides some difficulty in use. First, it is difficult to decompose the multiple factors of a test image, especially when the factor parameters are unknown or are not in the training set. Second, for face recognition and face synthesis tasks, it is also difficult to construct reliable multilinear models which have more than two factors. In this paper, we propose a novel tensor factorization method to decompose mixing factors for unseen test images. We set up tensor factorization problem as a least squares problems with a quadratic equality constraint, and solve it using numerical optimization techniques. The novelty in our approach compared to previous work is that our tensor factorization method does not require any knowledge or assumption of test images; we can attain parameters of facial factors by our tensor factorization method. We have conducted several experiments to show the versatility of the method for both face recognition and synthesis tasks. Thus, we demonstrate the proposed method produces reliable results for trilinear models as well as bilinear models.

关键词： Tensile stress Robustness Face recognition Testing Matrix decomposition Image recognition Least squares methods Constraint optimization Lighting Performance analysis

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Practical Methods for Geometric and Photometric Correction of Tiled Projector

Practical Methods for Geometric and Photometric Correction o...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： M. Harville B. Culbertson I. Sobel D. Gelb A. Fitzhugh D. Tanguay Hewlett Packard Laboratories Palo Alto CA USA

We describe a novel, practical method to create largescale, immersive displays by tiling multiple projectors on curved screens. Calibration is performed automatically with imagery from a single uncalibrated camera, without requiring knowledge of the 3D screen shape. Composition of 2D-mesh-based coordinate mappings, from screen-tocamera and from camera-to-projectors, allows image distortions imposed by the screen curvature and camera and projector lenses to be geometrically corrected together in a single non-parametric framework. For screens that are developable surfaces, we show that the screen-to-camera mapping can be determined without some of the complication of prior methods, resulting in a display on which imagery is undistorted, as if physically attached like wallpaper. We also develop a method of photometric calibration that unifies the geometric blending, brightness scaling, and black level offset maps of prior approaches. The functional form of the geometric blending is novel in itself. The resulting method is more tolerant of geometric correction imprecision, so that visual artifacts are significantly reduced at projector edges and overlap regions. Our efficient GPUbased implementation enables a single PC to render multiple high-resolution video streams simultaneously at frame rate to arbitrary screen locations, leaving the CPU largely free to do video decompression and other processing.

关键词： Photometry Large screen displays Cameras Calibration Brightness computer vision computer displays Laboratories Shape Lenses

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Pose-Invariant Physiological Face recognition in the Thermal Infrared Spectrum

Pose-Invariant Physiological Face Recognition in the Thermal...

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： P. Buddharaju I.T. Pavlidis P. Tsiamyrtzis Department of Computer Science University of Houston USA Department of Statistics Athens University of Economics and Business Greece

We present a novel framework for face recognition based on physiological information. The motivation behind this effort is to capitalize on the permanency of innate characteristics that are under the skin. To establish feasibility, we propose a specific methodology to capture facial physiological patterns using the bioheat information contained in thermal imagery. First, the algorithm delineates the human face from the background using the Bayesian framework. Then, it localizes the superficial blood vessel network using image morphology. The extracted vascular network produces contour shapes that are characteristic to each individual. The branching points of the skeletonized vascular network are referred to as Thermal Minutia Points (TMP) and constitute the feature database. To render the method robust to facial pose variations we collect for each subject to be stored in the database five (5) different pose images (center, mid-left profile, left profile, mid-right profile, and right profile). During the classification stage, the algorithm first estimates the pose of the test image. Then, it matches the local and global TMP structures extracted from the test image with those of the corresponding pose images in the database. We have conducted experiments on a sizeable database of thermal facial images collected in our lab. The good experimental results show that the proposed methodology has merit. More important, the results demonstrate the feasibility of the physiological framework in face recognition and open the way for further methodological and experimental research in the area.

关键词： Face recognition Infrared spectra Image databases Spatial databases Testing Skin Humans Bayesian methods Blood vessels Biomedical imaging

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Video Annotation by Active Learning and Cluster Tuning

Video Annotation by Active Learning and Cluster Tuning

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IEEE computer Society conference on computer vision and pattern recognition workshops (cvprw)

作者： Guo-jun Qi Yan Song Xian-Sheng Hua Hong-Jiang Zhang Li-Rong Dai Department of Automation University of Science and Technology Hefei Anhui China Department of EEIS University of Science and Technology Hefei Anhui China Microsoft Research Asia Beijing China

Supervised and semi-supervised learning are frequently applied methods to annotate videos by map..ing low-level features into high-level semantic concepts. Though they work well for certain concepts, the performance is still far from reality due to the large gap between the features and the semantics. The main constraint of these methods is that the information contained in a limited number of labeled training samples can hardly represent the distributions of the semantic concepts. In this paper, we propose a novel semi-automatic video annotation framework, active learning with clustering tuning, to tackle the disadvantages of current video annotation solutions. In this framework, firstly an initial training set is constructed based on clustering the entire video dataset. And then a SVM-based active learning scheme is proposed, which aims at maximizing the margin of the SVM classifier by manually selectively labeling a small set of samples. Moreover, in each round of active learning, we tune/refine the clustering results based on the prediction results of current stage, which is beneficial for selecting the most informative samples in the active learning process, as well as helps further improve the final annotation accuracy in the post-processing step. Experimental results show that the proposed scheme performs superior to typical active learning algorithms in terms of both annotation accuracy and stability.

关键词： Support vector machines Support vector machine classification Clustering algorithms Histograms Spatial databases Automation Asia computer vision pattern recognition conferences

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