3D face recognition has lately been attracting ever increasing attention. In this paper we review the full spectrum of 3D face processing technology, from sensing to recognition. The review covers 3D face modelling, 3...
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In this paper we develop a design methodology for generating efficient, target specific Hardware Description Language (HDL) code from an algorithm through the use of coarse-grain reconfigurable dataflow graphs as a re...
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Subspace. methods such as PCA, LDA. ICA have become, a standard tool to perform visual learning and recognition. In this paper we propose Representational Oriented Component Analysis (ROCA). an extension of OCA. to pe...
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ISBN:
(纸本)0769523722
Subspace. methods such as PCA, LDA. ICA have become, a standard tool to perform visual learning and recognition. In this paper we propose Representational Oriented Component Analysis (ROCA). an extension of OCA. to perform face recognition when just one sample per training class is available. Several novelties are introduced in order to improve generalization and efficiency: Combining several OCA classifiers based on different image representations of the unique training sample is shown to greatly improve the recognition performance. To improve generalization and to account for small misregistration effect, a learned subspace is added to constrain the OCA solution. A stable/efficient generalized eigenvector algorithm that solves the small size sample problem and avoids overfittmg. Preliminary experiments in the FRGC Ver 1.0 dataset (http://***/) show that ROCA outperforms existing linear techniques (PCA,OCA) and some commercial systems.
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 obs...
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We introduce a new method that characterizes typical local image features (e.g., SIFT [9], phase feature [3]) in terms of their distinctiveness, detectability, and robustness to image deformations. This is useful for ...
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ISBN:
(纸本)0769523722
We introduce a new method that characterizes typical local image features (e.g., SIFT [9], phase feature [3]) in terms of their distinctiveness, detectability, and robustness to image deformations. This is useful for the task of classifying local image features in terms of those three properties. The importance of this classification process for a recognition system using local features is as follows: a) reduce the recognition time due to a smaller number of features present in the test image and in the database of model features;b) improve the recognition accuracy since only the most useful features for the recognition task are kept in the model database;and c) increase the scalability of the recognition system given the smaller number of features per model. A discriminant classifier is trained to select well behaved feature points. A regression network is then trained to provide quantitative models of the detection distributions for each selected feature point. It is important to note that both the classifier and the regression network use image data alone as their input. Experimental results show that the use of these trained networks not only improves the performance of our recognition system, but it also significantly reduces the computation time for the recognition process.
This paper presents a multi-perspective (i.e., four camera views) multi-modal (i.e., thermal infrared and color) video based system for robust and real-time 3D tracking of important body *** multi-perspective characte...
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Development of a practical stereo vision sensor for real-world applications must account for the variability of high-volume production processes and the impact of unknown environmental conditions during its operation....
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We introduce a novel technique for performing radiometric compensation for a projector-camera system that projects images onto a textured planar surface, which is designed to minimize perceptual artifacts visible to o...
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Object recognition is a central problem in computervision research. Most object recognition systems have taken one of two approaches, using either global or local features exclusively. This may be in part due to the ...
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We introduce a novel user interface solution for mobile devices which enables the display to be controlled by the motion of the user's hand. A feature-based approach is proposed for dominant global motion estimati...
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