Robust Appearance-based Tracking using a sparse Bayesian classifier
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: Real-Time Adaptive Hand Motion Recognition Using a Sparse Bayesian Classifier
abstract: An approach to increase adaptability of a recognition system, which can recognise 10 elementary gestures and be extended to sign language recognition, is proposed. In this work, recognition is done by firstly extracting a motion gradient orientation image from a raw video input and then classifying a feature vector generated from this image to one of the 10 gestures by a sparse Bayesian classifier. The classifier is designed in a way that it supports online incremental learning and it can be thus re-trained to increase its adaptability to an input captured under a new condition. Experiments show that the accuracy of the classifier can be boosted from less than 40% to over 80% by re-training it using 5 newly captured samples from each gesture class. Apart from having a better adaptability, the system can work reliably in real-time and give a probabilistic output that is useful in complex motion analysis.

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: A Distributed Approach to Musical Composition
abstract: Current techniques for automated composition use a single algorithm, focusing on one aspect of musical generation. In our system we make use of several algorithms, distributed using an agent oriented middleware, with each specialising on a separate aspect of composition. This paper describes the architecture and algorithms behind this system, with a focus on the agent framework used for implementation. We show early results which encourage a future application of this framework in automated music composition and analysis.

title: SmartSiren: virus detection and alert for smartphones
abstract: Smartphones have recently become increasingly popular because they provide "all-in-one" convenience by integrating traditional mobile phones with handheld computing devices. However, the flexibility of running third-party softwares also leaves the smartphones open to malicious viruses. In fact, hundreds of smartphone viruses have emerged in the past two years, which can quickly spread through various means such as SMS/MMS, Bluetooth and traditional IP-based applications. Our own implementations of two proof-of-concept viruses on Windows Mobile have confirmed the vulnerability of this popular smartphone platform.
 In this paper, we present SmartSiren, a collaborative virusdetection and alert system for smartphones. In order to detect viruses, SmartSiren collects the communication activity information from the smartphones, and performs joint analysis to detect both single-device and system-wide abnormal behaviors. We use a proxy-based architecture to offload the processing burden from resource-constrained smartphones and simplify the collaboration among smartphones. When a potential virus is detected, the proxy quarantines the out-break by sending targeted alerts to those immediately threatened smartphones. We have demonstrated the feasibility of SmartSiren through implementations on a Dopod 577w smartphone, and evaluated its effectiveness using simulations driven by 3-week SMS traces from a national cellular carrier. Our results show that SmartSiren can effectively prevent wide-area virus outbreaks with affordable overhead.

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: Stability Analysis of RED Gateway with Multiple TCP Reno Connections
abstract: It has been observed that a bottleneck random early detection (RED) gateway becomes oscillatory when regulating a flow in multiple TCP connections. The stability boundary of the TCP-RED system depends on various network parameters, making the adjustment of the RED gateway a difficult task. Based on a fluid-flow model, analytical conditions were formulated that describe the stable boundary of the RED gateway depending on the number of TCP Reno connections. The proposed model accurately generates a stability boundary surface in a four dimensional space, which facilitates the adjustment of parameters for stable operation of the RED gateway. The accuracy of the analytical results has been verified using the ns-2 network simulations.

title: Complete Coverage by Mobile Robots Using Slice Decomposition Based on Natural Landmarks
abstract: In applications such as vacuum cleaning, painting, demining and foraging, a mobile robot must cover an unknown surface. The efficiency and completeness of coverage is improved by the construction of a map while the robot covers the surface. Existing methods generally use grid maps, which are susceptible to odometry error and may require considerable memory and computation. We propose a new "slice decomposition" ideally suited to coverage by a simple zigzag path. Cell boundaries are large, easily detectable natural landmarks. Therefore, the decomposition is robust against uncertainty in sensors. It can also handle a wider variety of environments. The proposed method has been evaluated using simulation and real robot experiments.