In order to improve the performance of estimating the fundamental matrix, a key problem arising in stereo vision, a novel method based on stripe constraints is presented. In contrast to traditional methods based on al...In order to improve the performance of estimating the fundamental matrix, a key problem arising in stereo vision, a novel method based on stripe constraints is presented. In contrast to traditional methods based on algebraic least-square algorithms, the proposed approach aims to minimize a cost function that is derived from the minimum radius of the Hough transform. In a structured-light system with a particular stripe code pattern, there are linear constraints that the points with the same code are on the same surface. Using the Hough transform, the pixels with the same code map to the Hough space, and the radius of the intersections can be defined as the evaluation function in the optimization progress. The global optimum solution of the fundamental matrix can be estimated using a Levenberg- Marquardt optimization iterative process based on the Hough transform radius. Results illustrate the validity of this algorithm, and prove that this method can obtain good performance with high efficiency.展开更多
Symbolic analysis has many applications in the design of analog circuits. Existing approaches rely on two forms of symbolic-expression representation: expanded sum-of-product form and arbitrarily nested form. Expanded...Symbolic analysis has many applications in the design of analog circuits. Existing approaches rely on two forms of symbolic-expression representation: expanded sum-of-product form and arbitrarily nested form. Expanded form suffers the problem that the number of product terms grows exponentially with the size of a circuit. Nested form is neither canonical nor amenable to symbolic manipulation. In this paper, we present a new approach to exact and canonical symbolic analysis by exploiting the sparsity and sharing of product terms. This algorithm, called totally coded method (TCM), consists of representing the symbolic determinant of a circuit matrix by code series and performing symbolic analysis by code manipulation. We describe an efficient code-ordering heuristic and prove that it is optimum for ladder-structured circuits. For practical analog circuits, TCM not only covers all advantages of the algorithm via determinant decision diagrams (DDD) but is more simple and efficient than DDD method.展开更多
文摘In order to improve the performance of estimating the fundamental matrix, a key problem arising in stereo vision, a novel method based on stripe constraints is presented. In contrast to traditional methods based on algebraic least-square algorithms, the proposed approach aims to minimize a cost function that is derived from the minimum radius of the Hough transform. In a structured-light system with a particular stripe code pattern, there are linear constraints that the points with the same code are on the same surface. Using the Hough transform, the pixels with the same code map to the Hough space, and the radius of the intersections can be defined as the evaluation function in the optimization progress. The global optimum solution of the fundamental matrix can be estimated using a Levenberg- Marquardt optimization iterative process based on the Hough transform radius. Results illustrate the validity of this algorithm, and prove that this method can obtain good performance with high efficiency.
文摘Symbolic analysis has many applications in the design of analog circuits. Existing approaches rely on two forms of symbolic-expression representation: expanded sum-of-product form and arbitrarily nested form. Expanded form suffers the problem that the number of product terms grows exponentially with the size of a circuit. Nested form is neither canonical nor amenable to symbolic manipulation. In this paper, we present a new approach to exact and canonical symbolic analysis by exploiting the sparsity and sharing of product terms. This algorithm, called totally coded method (TCM), consists of representing the symbolic determinant of a circuit matrix by code series and performing symbolic analysis by code manipulation. We describe an efficient code-ordering heuristic and prove that it is optimum for ladder-structured circuits. For practical analog circuits, TCM not only covers all advantages of the algorithm via determinant decision diagrams (DDD) but is more simple and efficient than DDD method.
