Издательство Springer, 1993, -499 pp.An image or video sequence is a series of two-dimensional (2-D) images sequentially ordered in time. Image sequences can be acquired, for instance, by video, motion picture, X-ray, or acoustic cameras, or they can be synthetically generated by sequentially ordering 2-D still images as in computer graphics and animation. The use of image sequences in areas such as entertainment, visual communications, multimedia, education, medicine, surveillance, remote control, and scientific research is constantly growing as the use of television and video systems are becoming more and more common. The boosted interest in digital video for both consumer and professional products , along with the availability of fast processors and memory at reasonable costs, has been a major driving force behind this growth. Before we elaborate on the two major terms that appear in the title of this book, namely motion analysis and image sequence processing, we like to place them in their proper contexts within the range of possible operations that involve image sequences. In this book, we choose to classify these operations into three major categories, namely (i) image sequence processing, (ii) image sequence analysis, and (iii) visualization . The interrelationship among these three categories is pictorially described in Figure below in the form of an "ima.ge sequence triangle". Image sequence processing, which is essentially a sequence-in and sequence-out operation, refers to the operations of filtering , spatiotemporal interpolation and subsampling, and compression of image sequences, aimed at improving the (visual) image quality, conversion between different video formats, and bandwidth-efficient representation of image sequences, respectively. The second category is image sequence analysis, referring to those operations that generate some type of data from image sequences for the purpose of information retrieval or interpretation. Motion analysis is an important branch of image sequence analysis. It refers to estimation of the image motion (the projection of the 3-D motion onto the 2-D image plane, or optical flow), inference of the 3-D object motion, depth information, as well as the surface characteristics of objects present in the actual 3-D scene. Motion information is utilized not only in various analysis tasks such as segmentation, pattern recognition and tracking, and scene interpretation, but is also instrumental in image sequence processing, as pointed out in Figure. The third category of operations that involves image sequences is visualization. It is concerned with generating image sequences on the basis of data which is not readily in the form of an image sequence. Computer graphics, virtual reality, and several emerging methods for scientific data visualization belong to this category. This book focuses on motion analysis and image sequence processing, and the use of motion analysis in developing efficient and powerful image sequence processing algorithms .Hierarchical Model-Based Motion Estimation An Estimation Theoretic Perspective on Image Processing and the Calculation of Optical Flow Estimation of 2-D Motion Fields from Image Sequences with Application to Motion-Compensated Processing Edge-Based 3-D Camera Motion Estimation with Application to Video Coding Motion Compensation: Visual Aspects, Accuracy, and Fundamental Limits Motion Field Estimators and Their Application to Image Interpolation Subsampling of Digital Image Sequences Using Motion Information Image Sequence Coding Using Motion-Compensated Subband Decomposition Vector Quantization for Video Data Compression Model-Based Image Sequence Coding Human Facial Motion Analysis and Synthesis with Applications to Model-Based Coding Motion Compensated Spatiotemporal Kalman Filter Multiframe Wiener Restoration of Image Sequences 3-D Median Struсtures for Image Sequence Filtering and Coding Video Compression for Digital ATV Systems
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