Object Assisted Video Coding for Video Conferencing System
An object-based video coding for video conferencing system is proposed. There are two main processes: segmentation process and face detection process. The segmentation process is used to segment each frame of a video sequence into two non-overlapping regions, namely foreground and background. A novel face detection technique based on chrominance and the contour of the segmented region is applied to the foreground region. Smaller quantization step is used for the facial region to improve viewer's perception while a larger quantization step is used for the background to compensate the coding efficiency. The remaining regions are kept in normal coding quality to prevent degradation of important information other than the facial regio.

title: Fast analytical approach to finding steady-state waveforms for power electronics circuits using orthogonal polynomial basis functions
abstract: This paper describes a general analytical procedure for steady-state waveform analysis of power electronics circuits using orthogonal polynomials. The proposed method exploits the time-domain piecewise property of power electronics circuits as well as the orthogonality of certain polynomials in order to maximize the accuracy and computational efficiency. This new analytical approach can provide a fast means to obtain improved and more robust solutions of steady-state waveforms of power electronics circuits

title: Continuous Gesture Recognition using a Sparse Bayesian Classifier
abstract: An approach to recognise and segment 9 elementary gestures from a video input is proposed and it can be applied to continuous sign recognition. An isolated gesture is recognised by first converting a portion of video into a motion gradient orientation image and then classifying it into one of the 9 gestures by a sparse Bayesian classifier. The portion of video used is decided by using a sampling technique based on condensation framework. By doing so, gestures can be segmented from the video in a probabilistic manner. Experiments show that the proposed method can achieve accuracy around 90% in both isolated and continuous gesture recognition without using special equipment such as glove devices and the system can run in real-time

title: Cluster Computing and Grid 2005 Works in Progress
abstract: This is the second in a two-part series () of works-in-progress articles taken from a special session, which was part of the Cluster Computing and Grid 2005 conference (http://www.cs.cf.ac.uk/ccgrid2005), held in Cardiff, UK. The session was organized by Mark Baker (University of Portsmouth, UK) and Daniel S. Katz (. For more information, you can contact the session organizers or the authors of the articles.

title: Robust Appearance-based Tracking using a sparse Bayesian classifier
abstract: An appearance-based approach to track an object that may undergo appearance change is proposed. Unlike recent methods that store a detailed representation of object's appearance, this method allows an appearance feature with a reduced dimension to be used. Through the use of a sparse Bayesian classifier, high classification and detection accuracy can be maintained even if a reduced feature vector is used. In addition, the classifier allows online-training which enables online-updating of the original classification model and provides better adaptability. Experiments show that the method can be used to track targets undergoing appearance change due to the change in view-point, facial expression and lighting direction

title: Design patterns for games
abstract: Designing a two-person game involves identifying the game model to compute the best moves, the user interface (the "view") to play the game, and the controller to coordinate the model and the view. A crucial task is to represent the algorithms used in their highest abstract forms. This can prove to be a difficult and subtle endeavor. It is made easier however by the use of good object-oriented (OO) design principles to help maintain a high level abstract viewpoint during the design process. The state pattern is used to represent the game board and is coupled with the visitor pattern to provide state-dependent, variant behaviors. The min-max algorithm and its variants are implemented as the strategy pattern, which allows flexible and extensible computational capability. Careful analysis is performed to properly abstract the interactions between the model and the view. The command design pattern is used to provide callback services between the model and the view. Leading students through this design process enables them to learn algorithms and architectures that easily scale to full-sized applications.

title: Characterizing flows in large wireless data networks
abstract: Several studies have recently been performed on wireless university campus networks, corporate and public networks. Yet little is known about the flow-level characterization in such networks. In this paper, we statistically characterize both static flows and roaming flows in a large campus wireless network using a recently-collected trace. For static flows, we take a two-tier approach to characterizing the flow arrivals, which results a Weibull regression model. We further discover that the static flow arrivals in spatial proximity show strong similarity. As for roaming flows, they can also be well characterized statistically.We explain the results by user behaviors and application demands, and further cross-validate the modeling results by three other traces. Finally, we use two examples to illustrate how to apply our models for performance evaluation in the wireless context.