Spatial-temporal feature learning is of vital importance for video emotion recognition. Previous deep network structures often focused on macro-motion which extends over long time scales, e.g., on the order of seconds...
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Capturing real motions from video sequences is a powerful method for automatic building of facial articulation models. In this paper, we propose an explanation-based facial motion tracking algorithm based on a piecewi...
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Capturing real motions from video sequences is a powerful method for automatic building of facial articulation models. In this paper, we propose an explanation-based facial motion tracking algorithm based on a piecewise Bezier volume deformation model (PBVD). The PBVD is a suitable model both for the synthesis and the analysis of facial images. It is linear and independent of the facial mesh structure. With this model, basic facial movements, or action units, are interactively defined. By changing the magnitudes of these action units, animated facial images are generated. The magnitudes of these action units can also be computed from real video sequences using a model-based tracking algorithm. However, in order to customize the articulation model for a particular face, the predefined PBVD action units need to be adaptively modified. In this paper, we first briefly introduce the PBVD model and its application in facial animation. Then a multiresolution PBVD-based motion tracking algorithm is presented. Finally, we describe an explanation-based tracking algorithm that takes the predefined action units as the initial articulation model and adaptively improves them during the tracking process to obtain a more realistic articulation model. Experimental results on PBVD-based animation, model-based tracking, and explanation-based tracking are shown in this paper.
We study the problem of representing images within a multimedia Database Management System (DBMS), in order to support fast retrieval operations without compromising storage efficiency. To achieve this goal, we propos...
We study the problem of representing images within a multimedia Database Management System (DBMS), in order to support fast retrieval operations without compromising storage efficiency. To achieve this goal, we propose new image coding techniques which combine a wavelet representation, embedded coding of the wavelet coefficients, and segmentation of image-domain regions in the wavelet domain. A bitstream is generated in which each image region is encoded independently of other regions, without having to explicitly store information describing the regions. Simulation results show that our proposed algorithms achieve coding performance which compares favorably, both perceptually and objectively, to that achieved using state-of-the-art image/video coding techniques while additionally providing region-based support.
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