From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

http://cvssp-data.eps.surrey.ac.uk/Personal/AdrianHilton/Publications_files/survey_techrep.pdf

A survey of advances in vision-based human motion capture and analysis

http://pancamr.lecture.ub.ac.id/files/2012/02/A-survey-on-vision-based-human-action-recognition_Image-and-Vision-Computing_2010.pdf

A survey on vision-based human action recognition

Human activity recognition is an important area of computer vision research. Its applications include surveillance systems, patient monitoring systems, and a variety of systems that involve interactions between persons and electronic devices such as human-computer interfaces. Most of these applications require an automated recognition of high-level activities, composed of multiple simple (or atomic) actions of persons. This article provides a detailed overview of various state-of-the-art research papers on human activity recognition. We discuss both the methodologies developed for simple human actions and those for high-level activities. An approach-based taxonomy is chosen that compares the advantages and limitations of each approach. Recognition methodologies for an analysis of the simple actions of a single person are first presented in the article. Space-time volume approaches and sequential approaches that represent and recognize activities directly from input images are discussed. Next, hierarchical recognition methodologies for high-level activities are presented and compared. Statistical approaches, syntactic approaches, and description-based approaches for hierarchical recognition are discussed in the article. In addition, we further discuss the papers on the recognition of human-object interactions and group activities. Public datasets designed for the evaluation of the recognition methodologies are illustrated in our article as well, comparing the methodologies' performances. This review will provide the impetus for future research in more productive areas.

http://cvrc.ece.utexas.edu/Publications/review_ryoo_hdr.pdf

Human activity analysis: A review

A morphable model for the synthesis of 3D faces

The smart classroom integrates voice-recognition, computer-vision, and other technologies to provide a tele-education experience similar to a real classroom experience.

The smart classroom: merging technologies for seamless tele-education

The Ambient Kitchen is a high fidelity prototype for exploring the design of pervasive computing algorithms and applications for everyday environments. The environment integrates data projectors, cameras, RFID tags and readers, object mounted accelerometers, and under-floor pressure sensing using a combination of wired and wireless networks. The Ambient Kitchen is a lab-based replication of a real kitchen where careful design has hidden the additional technology, and allows both the evaluation of pervasive computing prototypes and the simultaneous capture of the multiple synchronized streams of sensor data. Previous work exploring the requirements for situated support for people with cognitive impairments motivated the design of the physical and technical infrastructure and we describe both our motivations and previous work on interaction design in kitchen environments. Finally, we describe how our lab-based prototype has been put to use as: a design tool for designers; a design tool for users; an observatory to collect sensor data for activity recognition algorithm development, and an evaluation test bed. The limitations and advantages of lab-based, as opposed to in situ home-based testing, are discussed

Ambient kitchen: designing situated services using a high fidelity prototyping environment

Visatram, a real-time vision system for automatic traffic monitoring

In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a low dimensional manifold and can be learned from training data. Based on this assumption, firstly we derived the dimensionality reduction and density estimation algorithm for unsupervised learning of object intrinsic representation, the obtained non-rigid part of object state reduces even to 2 dimensions. Secondly the dynamical model is derived and trained based on this intrinsic representation. Thirdly the learned intrinsic object structure is integrated into a particle-filter style tracker. We will show that this intrinsic object representation has some interesting properties and based on which the newly derived dynamical model makes particle-filter style tracker more robust and reliable. Experiments show that the learned tracker performs much better than existing trackers on the tracking of complex non-rigid motions such as fish twisting with self-occlusion and large inter-frame lip motion. The proposed method also has the potential to solve other type of tracking problems.

Learning object intrinsic structure for robust visual tracking

http://cell.missouri.edu/media/publications/1-s2.0-S1077314202909677-main.pdf

Guangyou Xu

Papers

The smart classroom: merging technologies for seamless tele-education

Ambient kitchen: designing situated services using a high fidelity prototyping environment

Visatram, a real-time vision system for automatic traffic monitoring

Learning object intrinsic structure for robust visual tracking

A Real-Time Approach to the Spotting, Representation, and Recognition of Hand Gestures for Human–Computer Interaction