Pose and structure estimation from a single image is a fundamental problem in machine vision and multiple sensor fusion and integration. In this paper we propose using rigid constraints described in different coordina...Pose and structure estimation from a single image is a fundamental problem in machine vision and multiple sensor fusion and integration. In this paper we propose using rigid constraints described in different coordinate frames to iteratively estimate structural and camera pose parameters. Using geometric properties of reflected correspondences we put forward a new concept, the reflected pole of a rigid transformation. The reflected pole represents a general analysis of transformations that can be applied to both 2D and 3D transformations. We demonstrate how the concept is applied to calibration by proposing an iterative method to estimate the structural parameters of objects. The method is based on a coarse-to-fine strategy in which initial estimation is obtained through a classical linear algorithm which is then refined by iteration. For a comparative study of performance, we also implemented an extended motion estimation algorithm (from 2D-2D to 3D-2D case) based on epipolar geometry.展开更多
We present novel vector permutation and branch reduction methods to minimize the number of execution cycles for bit reversal algorithms.The new methods are applied to single instruction multiple data(SIMD) parallel im...We present novel vector permutation and branch reduction methods to minimize the number of execution cycles for bit reversal algorithms.The new methods are applied to single instruction multiple data(SIMD) parallel implementation of complex data floating-point fast Fourier transform(FFT).The number of operational clock cycles can be reduced by an average factor of 3.5 by using our vector permutation methods and by 1.1 by using our branch reduction methods,compared with conventional im-plementations.Experiments on MPC7448(a well-known SIMD reduced instruction set computing processor) demonstrate that our optimal bit-reversal algorithm consistently takes fewer than two cycles per element in complex array operations.展开更多
文摘Pose and structure estimation from a single image is a fundamental problem in machine vision and multiple sensor fusion and integration. In this paper we propose using rigid constraints described in different coordinate frames to iteratively estimate structural and camera pose parameters. Using geometric properties of reflected correspondences we put forward a new concept, the reflected pole of a rigid transformation. The reflected pole represents a general analysis of transformations that can be applied to both 2D and 3D transformations. We demonstrate how the concept is applied to calibration by proposing an iterative method to estimate the structural parameters of objects. The method is based on a coarse-to-fine strategy in which initial estimation is obtained through a classical linear algorithm which is then refined by iteration. For a comparative study of performance, we also implemented an extended motion estimation algorithm (from 2D-2D to 3D-2D case) based on epipolar geometry.
文摘We present novel vector permutation and branch reduction methods to minimize the number of execution cycles for bit reversal algorithms.The new methods are applied to single instruction multiple data(SIMD) parallel implementation of complex data floating-point fast Fourier transform(FFT).The number of operational clock cycles can be reduced by an average factor of 3.5 by using our vector permutation methods and by 1.1 by using our branch reduction methods,compared with conventional im-plementations.Experiments on MPC7448(a well-known SIMD reduced instruction set computing processor) demonstrate that our optimal bit-reversal algorithm consistently takes fewer than two cycles per element in complex array operations.
