Adaptive motion selection for online hand-eye calibration
While a robot moves, online hand–eye calibration to determine the relative pose between the robot gripper/end-effector and the sensors mounted on it is very important in a vision-guided robot system. During online hand–eye calibration, it is impossible to perform motion planning to avoid degenerate motions and small rotations, which may lead to unreliable calibration results. This paper proposes an adaptive motion selection algorithm for online hand–eye calibration, featured by dynamic threshold determination for motion selection and getting reliable hand–eye calibration results. Simulation and real experiments demonstrate the effectiveness of our method.

title: 3D Motion Segmentation from Straight-Line Optical Flow
abstract: We present a closed form solution to the problem of segmenting multiple 3D motion models from straight-line optical flow. We introduce the multibody line optical flow constraint(MLOFC), a polynomial equation relating motion models and line parameters. We show that the motion models can be obtained analytically as the derivative of the MLOFC at the corresponding line measurement, without knowing the motion model associated with that line. Experiments on real and synthetic sequences are also presented.

title: A New Calibration Model and Method of Camera Lens Distortion
abstract: Lens distortion is one of the main factors affecting camera calibration. In this paper, a new model of camera lens distortion is presented, according to which lens distortion is governed by the coefficients of radial distortion and a transform from ideal image plane to real sensing array plane. The transform is determined by two angular parameters describing the pose and two linear parameters locating the position of the sensing array plane. Compared with the conventional ones, the new model has fewer parameters to be calibrated and more explicit physical meaning. Calibration method of the new model is also proposed. Experiments show that calibration results from the new model and method can correct lens distortion better than conventional ones

title: Motion segmentation of multiple translating objects from line correspondences
abstract: This paper presents an analytic approach to motion segmentation of multiple translating objects from line correspondences in three perspective views. The basic idea of our algorithm is to view the estimation of multiple translational motions as the estimation of a single, though more complex, multibody motion model that is then factored into the original models by polynomial differentiation. Experimental results on synthetic and real scenes are presented.

title: Motion segmentation of multiple translating objects using line correspondences
abstract: We present an algebraic approach to multibody motion segmentation from line correspondences. Given three perspective views containing multiple linearly moving objects, we demonstrate that after applying a polynomial embedding to the line correspondences, they became related by the so-called multibody line constraint of translational motions. We show how to linearly estimate the multibody trifocal epipole from line-line-line correspondences. The individual trifocal epipoles are then obtained from the derivatives of the multibody line constraint (up to an unknown factor). Given normalized trifocal epipoles, we can use any special clustering technique to obtain the clustering of the motions and the correspondences. The limitations of the proposed algorithm are also discussed. Experimental results on synthetic and real dynamic scenes are presented.

title: Camera Calibration from a Single Frame of Planar Pattern
abstract: A method to calibrate camera from a single frame of planar pattern is presented in this paper. For a camera model with four intrinsic parameters and visible lens distortion, the principal point and distortion coefficients are firstly determined through analysis of the distortion in an image. The distortion is then removed. Finally, the other intrinsic and extrinsic parameters of the camera are obtained through direct linear transform followed by bundle adjustment. Theoretically, the method makes it possible to analyze the calibration result at the level of a single frame. Practically, such a method provides a easy way to calibrate a camera used in industrial vision system on line and used in desktop vision system. Experimental results of both simulated data and real images validate the method.

title: Gait Planning Of Quadruped Robot Based On Third-Order Spline Interpolation
abstract: This paper presented a brief description for the gait planning of quadruped robot named Aibo ERS-7 which is a standard platform in the RoboCup 4-legged league. We approach a spline shaped locus to reduce the dimension of the parameter optimizing space and solve the problem of the significant bias between the planned locus and the real one. The result shows that the spline shaped locus is effective in finding the optimized locus shape in a short time. Finally, the robot achieves a gait faster than any previously known learned gait for Aibo

title: Towards outlier detection for high-dimensional data streams using projected outlier analysis strategy
abstract: Outlier detection is an important research problem in data mining that aims to discover useful abnormal and irregular patterns hidden in large data sets. Most existing outlier detection methods only deal with static data with relatively low dimensionality. Recently, outlier detection for high-dimensional stream data became a new emerging research problem. A key observation that motivates this research is that outliers in high-dimensional data are projected outliers, i.e., they are embedded in lower-dimensional subspaces. Detecting projected outliers from high-dimensional stream data is a very challenging task for several reasons. First, detecting projected outliers is difficult even for high-dimensional static data. The exhaustive search for the outlying subspaces where projected outliers are embedded is a NP problem. Second, the algorithms for handling data streams are constrained to take only one pass to process the streaming data with the conditions of space limitation and time criticality. The currently existing methods for outlier detection are found to be ineffective for detecting projected outliers in high-dimensional data streams. 
In this thesis, we present a new technique, called the Stream Project Outlier deTector (SPOT), which attempts to detect projected outliers in high-dimensional data streams. SPOT employs an innovative window-based time model in capturing dynamic statistics from stream data, and a novel data structure containing a set of top sparse subspaces to detect projected outliers effectively. SPOT also employs a multi-objective genetic algorithm as an effective search method for finding the outlying subspaces where most projected outliers are embedded. The experimental results demonstrate that SPOT is efficient and effective in detecting projected outliers for high-dimensional data streams. The main contribution of this thesis is that it provides a backbone in tackling the challenging problem of outlier detection for high-dimensional data streams. SPOT can facilitate the discovery of useful abnormal patterns and can be potentially applied to a variety of high demand applications, such as for sensor network data monitoring, online transaction protection, etc.

title: Dynamic Terrain LOD with Region Preservation in 3D Game Engine
abstract: In the outdoor 3D game, the terrain can be modified because of interaction. This brings two new complexities to render terrain in 3D game. The first lies in the real-time visualization of dynamic terrain, and the second is that the modified terrain surface need to be preserved. We present an algorithm for dynamic terrain LOD(DT LOD) with preserving region in 3D game engine. The algorithm uses a DAG to represent dependency relationship of vertices which split triangles, and employs an active vertices set to update triangles in two consecutive frames for improving rendering performance. The region LOD can be constructed according to the view direction and the distance between the viewpoint and regions. The results of experiments show that our algorithm has a effective performance during rendering terrain.

title: Model-Driven Program Transformation of a Large Avionics Framework
abstract: Model-driven approaches to software development, when coupled with a domain-specific visual language, assist in capturing the essence of a large system in a notation that is familiar to a domain expert. From a high-level domain-specific model, it is possible to describe concisely the configuration features that a system must possess, in addition to checking that the model preserves semantic properties of the domain. With respect to large legacy applications written in disparate programming languages, the primary problem of transformation is the difficulty of adapting the legacy source to match the evolving features specified in the corresponding model. This paper presents an approach for uniting model-driven development with a mature program transformation engine. The paper describes a technique for performing widespread adaptation of source code from transformation rules that are generated from a domain-specific modeling environment for a large avionics framework.

title: Enabling Safe Dynamic Component-Based Software Adaptation
abstract: Recomposable software enables a system to change its structure and behavior during execution, in response to a dynamic execution environment. This paper proposes an approach to ensure that such adaptations are safe with respect to system consistency. The proposed method takes into consideration dependency analysis for target components, specifically determining viable sequences of adaptive actions and those states in which an adaptive action may be applied safely. We demonstrate that the technique ensures safe adaptation (insertion, removal, and replacement of components) in response to changing external conditions in a wireless multicast video application.