Performance of optical flow techniques
International Journal of Computer Vision
Real-time quantized optimal flow
Real-Time Imaging - Special issue on computer vision motion analysis
Optical Flow Computation on Compute Unified Device Architecture
ICIAP '07 Proceedings of the 14th International Conference on Image Analysis and Processing
Biomedical image analysis on a cooperative cluster of GPUs and multicores
Proceedings of the 22nd annual international conference on Supercomputing
GPU-based multigrid: real-time performance in high resolution nonlinear image processing
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
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A correlation-based optical flow algorithm using Compute Unified Device Architecture (CUDA) technology to achieve fast motion-based image segmentation is described. Using CUDA, a 240 processor GPU implementation of an optimized correlation-based optical flow algorithm allows segmentation to be achieved at high frame rates on high-resolution video sequences. Details of the mapping of the optical flow segmentation algorithm onto the CUDA architecture as well as performance results are given. The performance of the algorithm is further characterized as a function of the search and correlation window radii.