A Composite Method to Extract Eye Contour
An eye contour extraction method which combines a simplied version of Active Shape Model(ASM) with a gradient method is proposed. Considering the large amount of calculations required by ASM, it is only used to extract eyelids. As iris is considered to have some more regular shape, the detection of iris is done by the simple but fast gradient method, which is improved by introducing gradient value to the weight matrix. Our detection method has been implemented in the C programming language and experimental results shows good accuracy and efficiency.

title: An XML-Based Implementation of Multimodal Affective Annotation
abstract: In simple cases, affective computing is a computational device recognizing and acting upon the emotions of its user or having (or simulating having) emotions of its own in complex cases. Multimodal technology is currently one of the hottest focuses in affective computing research. However, the lack of a large-scale multimodal database limits the research to some respective and scattered fields, such as affective recognition by video or by audio. This paper describes the development and implementation of an XML-based multimodal affective annotation system which is called MAAS (Multimodal Affective Annotation System). MAAS contains a hierarchical affective annotation model based on the 3-dimensional affect space derived from Mehrabian’s PAD temperament scale. The final annotation file is formed in XML format in order to interchange the resources with other research groups conveniently.

title: Color-based road detection in urban traffic scenes
abstract: Road detection is a key issue for autonomous driving in urban traffic. In this paper, after a brief overview of existing methods, we present a road-area detection algorithm based on color images. This algorithm is composed of two modules: boundaries are first estimated based on the intensity image and road areas are subsequently detected based on the full color image. In the first module, an edge image of the scene is analyzed to obtain the candidates for the left and right road borders and to delimit the area that will subsequently be used to compute the mean and variance of the Gaussian distribution, assumed to be obeyed by the color components of road surfaces. The second module effectively extracts the road area and reinforces boundaries that most appropriately fit the road-extraction result. The combination of these modules can overcome basic problems due to inaccuracies in edge detection based on the intensity image alone and due to the computational complexity of segmentation algorithms based on color images. Experimental results on real road scenes have substantiated the effectiveness of the proposed method.

title: Deception Detection Via Blob Motion Pattern Analysis
abstract: Deception dectection is one of the most difficult problems in affect recognition and expression research area. Recently, non-verbal methods of detecting deception have appeared to be promising.  presented a proof-of-concept study based on the blob analysis of some suspects' interviews and mock experiments video clips. In this paper, we present our recent research work in the direction of developing an automated deception detection system. We propose a blob motion pattern analysis approach to solve this problem.

title: Real-time pose estimation for outdoor mobile robots using range data
abstract: Pose estimation is a key issue in mobile robots and important to moving object tracking. In this paper, we present a tangent based hybrid pose estimation algorithm with real-time performance using range data from laser radar, which consists of Iterative Tangent weighted Closest Point (ITCP) and Hough transform based Tangent Angle Histogram (HTAH) algorithms to overcome problems with past methods, such as local minimum, aperture-like, and high computation problems. The algorithm has been tested on both synthetic and real range data in outdoor environments. Experimental results demonstrate its high accuracy, low computation, wide applicability and high robustness to aperture-like problems, occlusion and noise.

title: A Polygon Detection Algorithm for Robot Visual Servoing
abstract: The problem of detecting polygon structures in images arises in many applications, from building extraction to cryo-electron microscopy. In this paper, A polygon detection algorithm (PDA) based on line detection is proposed. First of all, we introduce a parallel thinning algorithm to eliminate useless feature points. Then the feature points are organized as disjoint feature contours. For each independent contour, we detect line segment candidates based on RANSAC algorithm. With these candidates, a polygon (triangle, rectangle or other polygons) is composed. Compared to the state-of-the-art shape detection algorithms, PDA is much faster and it can detect any polygons such as triangles, rectangles, etc. We introduce PDA to a 6DOFs robot visual servoing platform and the experimental results show that significant improvements in time efficiency and performance robustness of the proposed algorithm have been achieved.

title: On Covering a Bipartite Graph with Cycles
abstract: We conjectured in [H. Wang,  (1999), pp. 115--121] that, for each integer $k\geq 2$, there exists N(k) such that if G=(V1,V2;E) is a bipartite graph with $|V_1|=|V_2|=n\geq N(k)$ and d(x)+d(y)\geq n+k$ for each pair of nonadjacent vertices x and y of G with $x\in V_1$ and $y\in V_2$, then for any k independent edges e1, . . ., ek of G, there exist k vertex-disjoint cycles C1, . . . ,Ck in G such that $e_i\in E(C_i)$ for all $i\in\{1,\ldots ,k\}$ and $V(C_1\cup\cdots \cup C_k)=V(G)$. This conjecture is also verified for k=2 in [H. Wang,  (1999), pp. 115--121]. We prove this conjecture for k=3 in this paper.

title: Directed Bipartite Graphs Containing Every Possible Pair of Directed Cycles

title: MIMO Probability Density Function Control Using Simple LOG-MLP Neural Networks
abstract: This paper presents a new model for the control of multivariable output probability density function (PDF). Firstly, a Multi-Layer Perceptron (MLP) neural network is adopted to approximate the static output PDF of the MIMO systems. Nonlinear principal component analysis (NLPCA) is then used to reduce the order of the obtained static neural network model and the dynamics of the system is considered based on the lower-order model. After this, an integrated solution is provided to set up the system with lower-order dynamics for the purpose of stochastic distribution control. The controller design is then presented in detail. Finally, a simulation example is given to demonstrate the effectiveness of the method and encouraging results have been obtained.

title: A minimized zero mean entropy approach to networked control systems
abstract: A novel control method is proposed for networked control systems with nonlinear process, probably non-Gaussian process noise and time delays. The performance index of closed loop control system consists of entropy, mean value and control energy constraint. Two stochastic control methods for networked control systems are given under the same general frame. One method utilizes gradient optimal techniques to obtain an optimal control law, and the stability of closed loop systems is analyzed. The other method gives the optimal solution of control law directly. The implementation issues are emphasized. The sliding window techniques and non-parametric probability density function estimation techniques are employed to obtain the entropy of tracking error recursively. As a result, the controller can be on-line tuned. Finally, the methodology is illustrated by simulations.

title: Hardware Support for Prescient Instruction Prefetch
abstract: This paper proposes and evaluates hardware mechanisms for supporting prescient instruction prefetch — an approach to improving single-threaded application performance by using helper threads to perform instruction prefetch. We demonstrate the need for enabling store-to-load communication and selective instruction execution when directly pre-executing future regions of an application that suffer I-cache misses. Two novel hardware mechanisms, safe-store and YAT-bits, are introduced that help satisfy these requirements. This paper also proposes and evaluates .nite state machine recall, a technique for limiting pre-execution to branches that are hard to predict by leveraging a counted I-prefetch mechanism. On a research Itanium®SMT processor with next line and streaming I-prefetch mechanisms that incurs latencies representative of next generation processors, prescient instruction prefetch can improve performance by an average of 10.0% to 22% on a set of SPEC 2000 benchmarks that suffer significant I-cache misses. Prescient instruction prefetch is found to be competitive against even the most aggressive research hardware instruction prefetch technique: fetch directed instruction prefetch.