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The goal of this book is to provide the readers a comprehensive map towards the common goal of better analyzing and synthesizing the pedestrian movement in dense, heterogeneous crowds.

Traditionally, scientific fields have defined boundaries, and scientists work on research problems within those boundaries. However, from time to time those boundaries get shifted or blurred to evolve new fields. For instance, the original goal of computer vision was to understand a single image of a scene, by identifying objects, their structure, and spatial arrangements. This has been referred to as image understanding. Recently, computer vision has gradually been making the transition away from understanding single images to analyzing image sequences, or video understanding. Video understanding deals with understanding of video sequences, e. g. , recognition of gestures, activities, facial expressions, etc. The main shift in the classic paradigm has been from the recognition of static objects in the scene to motion-based recognition of actions and events. Video understanding has overlapping research problems with other fields, therefore blurring the fixed boundaries. Computer graphics, image processing, and video databases have obvious overlap with computer vision. The main goal of computer graphics is to gener- ate and animate realistic looking images, and videos. Researchers in computer graphics are increasingly employing techniques from computer vision to gen- erate the synthetic imagery. A good example of this is image-based rendering and modeling techniques, in which geometry, appearance, and lighting is de- rived from real images using computer vision techniques. Here the shift is from synthesis to analysis followed by synthesis.

The deployment of surveillance systems has captured the interest of both the research and the industrial worlds in recent years. The aim of this effort is to increase security and safety in several application domains such as national security, home and bank safety, traffic monitoring and navigation, tourism, and military applications. The video surveillance systems currently in use share one feature: A human operator must monitor them at all times, thus limiting the number of cameras and the area under surveillance and increasing cost. A more advantageous system would have continuous active warning capabilities, able to alert security officials during or even before the happening of a crime. Existing automated surveillance systems can be classified into categories according to:The environment they are primarily designed to observe;The number of sensors that the automated surveillance system can handle;The mobility of sensor.The primary concern of this book is surveillance in an outdoor urban setting, where it is not possible for a single camera to observe the complete area of interest. Multiple cameras are required to observe such large environments. This book discusses and proposes techniques for development of an automated multi-camera surveillance system for outdoor environments, while identifying the important issues that a system needs to cope with in realistic surveillance scenarios. The goal of the research presented in this book is to build systems that can deal effectively with these realistic surveillance needs.

Multimodal Video Characterization and Summarization is a valuable research tool for both professionals and academicians working in the video field.This book describes the methodology for using multimodal audio, image, and text technology to characterize video content. This new and groundbreaking science has led to many advances in video understanding, such as the development of a video summary. Applications and methodology for creating video summaries are described, as well as user-studies for evaluation and testing.

The goal of this book is to provide the readers a comprehensive map towards the common goal of better analyzing and synthesizing the pedestrian movement in dense, heterogeneous crowds.

By minimizing the rank of the matrix containing observations drawn from images, the authors demonstrate how to solve four fundamental computer vision problems, including video denosing, background subtraction, motion estimation, and activity recognition.

Recently, computer vision has gradually been making the transition away from understanding single images to analyz ing image sequences, or video understanding. Computer graphics, image processing, and video databases have obvious overlap with computer vision.

Presents research efforts in the area of content-based exploration of image and video data. The two key issues emphasized are "content-awareness" and "user-in-the-loop". This work provides a comprehensive review on algorithms for visual feature extraction based on color, texture, shape, and structure.

Recently, computer vision has gradually been making the transition away from understanding single images to analyz ing image sequences, or video understanding. Computer graphics, image processing, and video databases have obvious overlap with computer vision.

Recently, computer vision has gradually been making the transition away from understanding single images to analyzing image sequences, or video Video understanding deals with understanding of video understanding. Computer graphics, image processing, and video databases have obvi ous overlap with computer vision.

Recently, computer vision has gradually been making the transition away from understanding single images to analyzing image sequences, or video Video understanding deals with understanding of video understanding. Computer graphics, image processing, and video databases have obvi ous overlap with computer vision.

Multimodal Video Characterization and Summarization is a valuable research tool for both professionals and academicians working in the video field. This book describes the methodology for using multimodal audio, image, and text technology to characterize video content.

3D Face Processing: Modeling, Analysis and Synthesis introduces the frontiers of 3D face processing techniques. It reviews existing 3D face processing techniques, including techniques for 3D face geometry modeling;

Recently, computer vision has gradually been making the transition away from understanding single images to analyz ing image sequences, or video understanding. Computer graphics, image processing, and video databases have obvious overlap with computer vision.

Recently, computer vision has gradually been making the transition away from understanding single images to analyz ing image sequences, or video understanding. Computer graphics, image processing, and video databases have obvious overlap with computer vision.

Recently, computer vision has gradually been making the transition away from understanding single images to analyzing image sequences, or video understanding. Computer graphics, image processing, and video databases have obvious overlap with computer vision.