Real-Time Implementation of an Optical Flow Algorithm
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Hardware implementation of optical flow constraint equation using FPGAs
Computer Vision and Image Understanding
Accurate dense optical flow estimation using adaptive structure tensors and a parametric model
IEEE Transactions on Image Processing
FPGA-based real-time optical-flow system
IEEE Transactions on Circuits and Systems for Video Technology
Accurate Optical Flow Sensor for Obstacle Avoidance
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
Hi-index | 0.00 |
A tensor-based optical flow algorithm is presented in this paper. This algorithm uses a cost function that is an indication of tensor certainty to adaptively adjust weights for tensor computation. By incorporating a good initial value and an efficient search strategy, this algorithm is able to determine optimal weights in a small number of iterations. The weighting mask for the tensor computation is decomposed into rings to simplify a 2D weighting into 1D. The devised algorithm is well-suited for real-time implementation using a pipelined hardware structure and can thus be used to achieve real-time optical flow computation. This paper presents simulation results of the algorithm in software, and the results are compared with our previous work to show its effectiveness. It is shown that the proposed new algorithm automatically achieves equivalent accuracy to that previously achieved via manual tuning of the weights.