In this paper we discuss object detection when only a small number of training examples are given. Specifically, we show how to incorporate a simple prior on the distribution of natural images into support vector mach...
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Variations in pose, expression, illumination, aging and disguise are considered as major challenges in face recognition and several techniques have been proposed to address these challenges. Plastic surgery, on the ot...
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ISBN:
(纸本)9781424439942
Variations in pose, expression, illumination, aging and disguise are considered as major challenges in face recognition and several techniques have been proposed to address these challenges. Plastic surgery, on the other hand, is considered as an arduous research issue;however, it has not yet been studied either theoretically, or experimentally This paper focuses on analyzing the effect of plastic surgery in face recognition algorithms. The preliminary study provides an experimental and analytical comparison of face recognition algorithms on a plastic surgery, database of 506 individuals. The experimental results indicate that existing face recognition algorithms perform poorly when matching pre and post surgery face images. The results also suggest that it is imperative for future face recognition systems to be able to address this important issue and hence there is a need for more research in this important area.
A wide range of methods have been proposed to detect and recognize objects. However, effective and efficient multiviewpoint detection of objects is still in its infancy, since most current approaches can only handle s...
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We investigate the problem of learning the structure of an articulated object, i.e. its kinematic chain, from feature trajectories under affine projections. We demonstrate this possibility by proposing an algorithm wh...
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Faces represent complex, multidimensional, meaningful visual stimuli and developing a computational model for face recognition is difficult. We present a hybrid neural network solution which compares favorably with ot...
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ISBN:
(纸本)0818672587
Faces represent complex, multidimensional, meaningful visual stimuli and developing a computational model for face recognition is difficult. We present a hybrid neural network solution which compares favorably with other methods. The system combines local image sampling, a self-organizing map neural network, and a convolutional neural network. The self-organizing map provides a quantization of the image samples into a topological space where inputs that are nearby in the original space are also nearby in the output space, thereby providing dimensionality reduction and invariance to minor changes in the image sample, and the convolutional neural network provides for partial invariance to translation, rotation, scale, and deformation. The method is capable of rapid classification, requires only fast, approximate normalization and preprocessing, and consistently exhibits better classification performance than the eigenfaces approach on the database considered as the number of images per person in the training database is varied from 1 to 5. With 5 images per person the proposed method and eigenfaces result in 3.8% and 10.5% error respectively. The recognizer provides a measure of confidence in its output and classification error approaches zero when rejecting as few as 10% of the examples. We use a database of 400 images of 40 individuals which contains quite a high degree of variability in expression, pose, and facial details.
Illumination inconsistencies cause serious problems for classical computervision applications such as tracking and stereo matching. We present a new approach to model illumination variations using an Illumination Rat...
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Near regular textures are pervasive in man-made and natural world. Their global regularity and local randomness pose new difficulties to the state of the art texture analysis and synthesis algorithms. We carry out a s...
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Many problems in computervision involving recognition and/or classification can be posed in the general framework of supervised learning. There is however one aspect of image datasets, the high-dimensionality of the ...
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A demonstration of a software prototype, called VADIS, (Video Analysis, Display and Indexing System) is presented. The functionality of VADIS includes real-time indexing of incoming live video stream using color histo...
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ISBN:
(纸本)0818684976
A demonstration of a software prototype, called VADIS, (Video Analysis, Display and Indexing System) is presented. The functionality of VADIS includes real-time indexing of incoming live video stream using color histogram based frame differencing, non-real-time cut detection and indexing of Motion JPEG or MPEG-1 video files. It includes a feature to save the indices and the storyboard generated during the indexing process.
We present an approach for aligning a 3D deformable model to a single face image. The model consists of a set of sparse 3D points and the view-based patches associated with every point. Assuming a weak perspective pro...
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