Building the Software Infrastructure for Smart Classroom: From Open Agent Architecture (OAA) to Smart Platform
Smart Classroom is a Smart Space developed to enhance tele-education practice. This paper describes the considerations of bringing forward Smart Platform as the software infrastructure of Smart Classroom system, abandoning the former implementation based on OAA. As a multi-agent system for Smart Space, Smart Platform encompasses following features: spontaneous discovery of runtime environment, automatic management and resolving of agent dependencies, combination of delegated communication and peer-to-peer communication, etc. In addition, a surrogate agent on Smart Platform and Metaglue from MIT is now being developed to inter-connect Smart Classroom with MIT's Intelligent Room to extend their functionality.

title: Error analysis of pure rotation-based self-calibration
abstract: Self-calibration using pure rotation is a well-known technique and has been shown to be a reliable means for recovering intrinsic camera parameters. However, in practice, it is virtually impossible to ensure that the camera motion for this type of self-calibration is a pure rotation. In this paper, we present an error analysis of recovered intrinsic camera parameters due to the presence of translation. We derived closed-form error expressions for a single pair of images with nondegenerate motion; for multiple rotations for which there are no closed-form solutions, analysis was done through repeated experiments. Among others, we show that translation-independent solutions do exist under certain practical conditions. Our analysis can be used to help choose the least error-prone approach (if multiple approaches exist) for a given set of conditions.

title: Three-dimensional animated face modeling from stereo video
abstract: 3D modeling of human face has been an active research topic in computer vision and computer graphics communities. In this paper we develop a face-modeling system from calibrated stereo video input. The stereo configuration is chosen according to the characteristics of the face structure. For data capturing the subject sits in front of the calibrated stereo video cameras and rotates his/her head from front view to side view. Then we can create his/her 3D face model with realistic texture mapped, which is ready for MPEG-4 compatible facial animation, by adapting a generic wireframe model to the input. In deciding 3D face geometry we utilize two kinds of 2D information. One is the correspondence between stereo pair; the other is self-occluded contour. After some 3D points in the specific face are obtained from both image clues in different frames, RBF (Radius Basis Function) data interpolation is performed to decide its shape. Afterwards texture image is generated from the face geometry and video. Experiments show that satisfactory results can be reached with our system.

title: Learning-Based Tracking of Complex Non-Rigid Motion
abstract: This paper describes a novel method for tracking complex non-rigid motions by learning the intrinsic object structure.The approach builds on and extends the studies on non-linear dimensionality reduction for object representation,object dynamics modeling and particle filter style tracking.First,the dimensionality reduction and density estimation algorithm is derived for unsupervised learning of object intrinsic representation,and the obtained non-rigid part of object state reduces even to 2-3 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.It is shown 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.Extensive experiments are done on the tracking of challenging non-rigid motions such as fish twisting with selfocclusion,large inter-frame lip motion and facial expressions with global head rotation.Quantitative results are given to make comparisons between the newly proposed tracker and the existing tracker.The proposed method also has the potential to solve other type of tracking problems.

title: Hidden Markov Model Based Events Detection in Soccer Video
abstract: This paper presents an algorithm developed based on hidden Markov model for cues fusion and event inference in soccer video. Four events, shoot, foul, offside and normal playing, are defined to be detected. The states of the events are employed to model the observations of the five cues, which are extracted from the shot sequences directly. The experimental results show the algorithm is effective and robust in inferring events from roughly extracted cues.

title: Power domination in block graphs
abstract: The problem of monitoring an electric power system by placing as few measurement devices in the system as possible is closely related to the well-known domination problem in graphs. In 2002, Haynes et al. considered the graph theoretical representation of this problem as a variation of the domination problem. They defined a set S to be a power dominating set of a graph if every vertex and every edge in the system is monitored by the set S (following a set of rules for power system monitoring). The power domination number γp(G) of a graph G is the minimum cardinality of a power dominating set of G. This problem was proved NP-complete even when restricted to bipartite graphs and chordal graphs. In this paper, we present a linear time algorithm for solving the power domination problem in block graphs. As an application of the algorithm, we establish a sharp upper bound for power domination number in block graphs and characterize the extremal graphs.

title: Output hazard-free transition tests for silicon calibrated scan based delay testing
abstract: Architectural restrictions of scan greatly limit the effectiveness of traditional scan based delay tests. It has been recently shown that additional testing for delays on short paths using fast clocks can significantly lower DPM. However, accurately obtaining the needed timing information for such tests from simulation is extremely difficult. The simulations must not only accurately account for the effects of process parameter variations, but also power supply noise and crosstalk from the excessive switching activity of scan tests. We suggest that learning signal timing information on silicon to "calibrate" such tests can be much more accurate and cost effective. However, such an approach requires that the outputs of the applied tests be hazard free to avoid learning incorrect timing due to a glitch at the output. Simulation results presented here indicate that such output hazard free test can be obtained with an average coverage only about 10% below the transition delay fault coverage for both launch-on-shift (LOS) and launch-on-capture (LOG) modes

title: Delay Defect Characterization Using Low Voltage Test
abstract: For nanometer designs, many subtle defects lead to excessive delays in signal paths that cause reliability concerns. Traditional test-based diagnosis methods can only identify the failing nodes without the capability to tell the defect nature behind the observed delay faults. This differentiation is important for gathering accurate defect statistics for process improvement during yield ramp-up. In this paper we presented an effective delay defect analysis methodology that can quickly categorize the delay defects into either transistor related defects or resistive interconnect defects. The new delay defect/failure characterization method is based on low voltage test and delay defect detection in slack interval (DDSI) method. Experimental results were presented to validate the effectiveness of the new method. Practical considerations were also addressed for adoption of the methodology.

title: Surface modelling using fourth order geometric flows
abstract: We use two fourth order geometric partial differential equations to efficiently solve several surface modelling problems, including the surface blending, the N-sided hole filling and the free-form surface fitting with the G/sup 1/ boundary continuity. The nonlinear equations used include the surface diffusion flow and the Willmore flow. These nonlinear equations are discretized using the mixed finite element method based on the combination of the loop's basis and the linear basis. The proposed approach is simple, efficient and gives very desirable results.

title: Efficient Algorithms for Determining 3-D Bi-Plane Imaging Geometry
abstract: Biplane projection imaging is one of the primary methods for imaging and visualizing the cardiovascular system in medicine. A key problem in such a technique is to determine the imaging geometry (i.e., the relative rotation and translation) of two projections so that the 3-D structure can be accurately reconstructed. Based on interesting observations and efficient geometric techniques, we present in this paper new algorithmic solutions for this problem. Comparing with existing optimization-based approaches, our techniques yield better accuracy and have bounded execution time, thus is more suitable for on-line applications. Our techniques can easily detect outliers to further improve the accuracy.