IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance of optical flow techniques
International Journal of Computer Vision
A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion
International Journal of Computer Vision
Classification of optical flow by constraints
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Spatio-temporal optical flow statistics (STOFS) for activity classification
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
A Database and Evaluation Methodology for Optical Flow
International Journal of Computer Vision
International Journal of Computer Vision
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Most of the methods to compute optical flows are variational-technique-based methods, which assume that image functions have spatiotemporal continuities and appearance motions are small. In the viewpoint of the discrete errors of spatial- and time-differentials, the appropriate resolution for optical flow depends on both the resolution and the frame rate of images since there is a problem with the accuracy of the discrete approximations of derivatives. Therefore, for low frame-rate images, the appropriate resolution for optical flow should be lower than the resolution of the images. However, many traditional methods estimate optical flow with the same resolution as the images. Therefore, if the resolution of images is too high, down-sampling the images is effective for the variational-technique-based methods. In this paper, we analyze the appropriate resolutions for optical flows estimated by variational optical-flow computations from the viewpoint of the error analysis of optical flows. To analyze the appropriate resolutions, we use hierarchical structures constructed from the multi-resolutions of images. Numerical results show that decreasing image resolutions is effective for computing optical flows by variational optical-flow computations in low frame-rate sequences.