By Dmitry Goldgof, Alan C Bovik, Chang Wen Chen
This quantity of unique papers has been assembled to honour the achievements of Professor Thomas S. Huang within the zone of snapshot processing and picture research. Professor Huang's lifetime of inquiry has spanned a couple of a long time, as his paintings on imaging difficulties begun in 1960's. through the years, he has made many primary and pioneering contributions to almost each region of this box. Professor Huang has got quite a few awards, together with the distinguished Jack Kilby sign Processing Medal from IEEE. He has been elected to the nationwide Academy of Engineering, and named Fellow of IEEE, Fellow of OSA, Fellow of IAPR and Fellow of SPIE. Professor Huang has made basic contributions to photograph processing, trend popularity and computing device imaginative and prescient, together with: layout and balance try out of multidimensional electronic filters, electronic holography; compression concepts for records and photographs; 3D movement and modelling, research and visualization of the human face, hand and physique, multi-modal human-computer interfaces; and multimedia databases. This quantity is meant to spotlight his contributions by way of displaying the breadth of parts during which his scholars are operating. As such, contributed chapters have been written by means of a few of his many former graduate scholars (some with Professor Huang as a co-author) and illustrate not just his contributions to imaging technological know-how but additionally his dedication to academic endeavour. The breadth of contributions is a sign of impression of Professor Huang to the sphere of sign processing, picture processing, laptop imaginative and prescient and functions; there are chapters on studying in snapshot retrieval, facial movement research, cloud movement monitoring, wavelet coding, powerful video transmission, and lots of different themes. The appendix includes a number of reprints of Professor Huang's such a lot influential papers from the 1970's to 1990's. this article is designed for photograph processing researchers, together with educational school, graduate scholars and researchers, in addition to pros operating in program components.
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Extra resources for Advances in Image Processing and Understanding: A Festschrift for Thomas S. Huang
In our implementation, the template for each node consists of 11x11 pixels and the searching region is 17x17 pixels. To deal with the drifting problem, both the templates from the previous frame and the templates from the initial frame are used: the even nodes of a patch are tracked using the templates from the previous frame and the odd nodes are tracked using those of the initial frame. Our experiments showed that this approach is very effective. From the resulting motion vectors, 3D rigid motions and nonrigid motions (intensities of expressions/visemes or action units) are computed simultaneously using a least squares estimator.
It is basically the same as the block diagram for the model-based PBVD method except that an additional block is added to adjust the nonrigid motion model L. The model L consists of two parts: B and D . Both of them can be adjusted. Changing D means changing the displacement vector or control nodes for each action unit so that the model fits the data better. Modifying B means modifying Bezier volumes so that descriptive power of the model is enhanced. In this paper, we discuss the learning of D .
The two color bars on the right side of the image are Qc (left) and Q* (right), respectively. For the bimodal emotion recognition and the real-time tracking system, 12 action units are used. Users can design any set of deformation units for the tracking algorithm. These deformations can be either at expression level or at action unit level. Lip tracking results are shown in Figure 14. Figure 15 shows the results of the real-time tracker. Facial animation sequences are generated from the detected motion parameters.