Hidden Markov Model Based Events Detection in Soccer Video
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: Smart Remote Classroom: Creating a Revolutionary Real-Time Interactive Distance Learning System
abstract: Real-time interactive virtual classroom is an important type of distance learning. However currently available systems are insufficient in the support of large-scale user access, and neither can they accommodate accessing with heterogeneous devices and networks. Furthermore, these systems are usually desktop-based, which results that the teachers' experience is completely different from teaching in a real classroom. The Smart Remote Classroom project tackles these difficulties through the development of the following technologies: 1) A hybrid application-layer Multicast protocol called TORM and an Adaptive Content Delivery scheme called AMTM. Together they enable large-scale users to access a virtual classroom with different devices and networks at the same time. 2) A dedicated software called SameView, which take use of the proposed TORM and AMTM technology and provide a rich set of functions for teachers and students to efficiently carry out the real-time interactive distance learning. Moreover, SameView can record the whole process of a class into a compound multimedia document for later retrieval and review of the class. 3) An augmented classroom called Smart Classroom, where the user interface of the SameView for the teacher are distributed in and fused with the room space. Thus the teacher can instruct the remote students just like teaching face-to-face in a conventional classroom. All these technologies has been successfully integrated and demonstrated in the prototype 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: A Speaker Tracking Algorithm Based on Audio and Visual Information Fusion Using Particle Filter
abstract: Object tracking by sensor fusion has become an active research area in recent years, but how to fuse various information in an efficient and robust way is still an open problem. This paper presents a new algorithm for tracking speaker based on audio and visual information fusion using particle filter. A closed-loop architecture with reliability of each individual tracker is adopted, and a new method for data fusion and reliability adjustment is proposed. Experiments show the new algorithm is efficient in fusing information and robust to noise.

title: VISATRAM: a real-time vision system for automatic traffic monitoring
abstract: This paper presents a novel approach to automatic traffic monitoring using 2D spatio-temporal images. A TV camera is mounted above a highway to monitor the traffic through two slice windows, and a panoramic view image and an epipolar plane image are formed for each lane. Our real-time vision system for automatic traffic monitoring, VISATRAM, is an inexpensive system with a PC486 and a frame grabber. The system cannot only count vehicles and estimate their speeds but also classify them using 3D measurements. The system has been tested with real road images under various light conditions, including shadows in daytime and lights at night.

title: Efficient Fourier-Based Approach for Detecting Orientations and Occlusions in Epipolar Plane Images for 3D Scene Modeling
abstract: This paper presents a Fourier-based approach for automatically constructing a 3D panoramic model of a natural scene from a video sequence. The video sequences could be captured by an unstabilized camera mounted on a moving platform on a common road surface. As the input of the algorithms, “seamles” panoramic view images (PVIs) and epipolar plane images (EPIs) are generated after image stabilization if the camera is unstabilized. A novel panoramic EPI analysis method is proposed that combines the advantages of both PVIs and EPIs efficiently in three important steps: locus orientation detection in the Fourier frequency domain, motion boundary localization in the spatio-temporal domain, and occlusion/resolution recovery only at motion boundaries. The Fourier energy-based approaches in literature were usually for low-level local motion analysis and are therefore not accurate for 3D reconstruction and are also computationally expensive. Our panoramic EPI analysis approach is both accurate and efficient for 3D reconstruction. Examples of layered panoramic representations for large-scale 3D scenes from real world video sequences are given.

title: Automatic reconstruction of surfaces and scalar fields from 3D scans
abstract: We present an efficient and uniform approach for the automatic reconstruction of surfaces of CAD (computer aided design) models and scalar fields defined on them, from an unorganized collection of scanned point data. A possible application is the rapid computer model reconstruction of an existing part or prototype from a three dimensional (3D) points scan of its surface. Color, texture or some scalar material property of the physical part, define natural scalar fields over the surface of the CAD model. Our reconstruction algorithm does not impose any convexity or differentiability restrictions on the surface of the original physical part or the scalar field function, except that it assumes that there is a sufficient sampling of the input point data to unambiguously reconstruct the CAD model. Compared to earlier methods our algorithm has the advantages of simplicity, efficiency and uniformity (both CAD model and scalar field reconstruction). The simplicity and efficiency of our approach is based on several novel uses of appropriate sub-structures (alpha shapes) of a three-dimensional Delaunay Triangulation, its dual the three-dimensional Voronoi diagram, and dual uses of trivariate Bernstein-Bezier forms. The boundary of the CAD model is modeled using implicit cubic Bernstein-Bezier patches, while the scalar field is reconstructed with functional cubic Bernstein-Bezier patches.

title: Regular algebraic curve segments (III) - applications in interactive design and data fitting
abstract: In this paper (part three of the trilogy) we use low degree G 1 and G 2 continuous regular algebraic spline curves defined within parallelograms, to interpolate an ordered set of data points in the plane. We explicitly characterize curve families whose members have the required interpolating properties and possess a minimal number of inflection points. The regular algebraic spline curves considered here have many attractive features: They are easy to construct. There exist convenient geometric control handles to locally modify the shape of the curve. The error of the approximation is controllable. Since the spline curve is always inside the parallelogram, the error of the fit is bounded by the size of the parallelogram. The spline curve can be rapidly displayed, even though the algebraic curve segments are implicitly defined.

title: Delay Test Scan Flip-Flop: DFT for High Coverage Delay Testing
abstract: Scan based delay testing is currently mostly implemented using launch-on-capture (LOC) delay tests. Launch-on-shift (LOS) tests are generally more effective, achieving higher fault coverage with significantly fewer test vectors, but require a fast scan enable, which is not supported by most designs. The paper presents low cost solution for implementing LOS tests by adding a small amount of logic (six transistors) in each flip-flop to align the slow scan enable signal to the clock edge. The new design can support full LOS and LOC testing, achieving an average TDF coverage of 92.67% in this combined mode for the ISCAS89 benchmarks. Adding a second slow global scan enable signal also allows mixed LOC/LOS tests, which can further increase coverage up to 94.86% on average for ISCAS89 benchmarks

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.

title: An Efficient Algorithm for Determining 3-D Bi-plane Imaging Geometry
abstract: Biplane projection imaging is one of the primary methods for imaging and visualizing the cardiovascular systems in medicine. A key problem in such a technique is to determine the imaging geometry (i.e., the 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 a new algorithmic solution for this problem. Comparing with existing optimization-based approaches, our technique yields better accuracy, has bounded execution time, and thus is more suitable for on-line applications. Our technique can easily deal with outliers for further improving the accuracy.