An Adaptive Multiscale Scheme for Real-Time Motion Field Estimation

R. Battiti
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Abstract

The problem considered in this work is that of estimating the motion field (i.e. the projection of the velocity field onto the image plane) from a temporal sequence of images. Generic images contain different objects with diverse spatial frequencies and motion amplitudes. To deal with this complex environment in a fast and effective way, biological visual systems use parallel processing, visual channels at different resolutions and adaptive mechanisms. In this paper a new adaptive multiscale scheme is proposed, in which the spatial discretization scale is based on a local estimate of the errors involved. Considering the constraints for real-time operation, flexibility and portability, the scheme can be implemented on MIMD parallel computers with medium size grains with high efficiency. Tests with ray-traced and video-acquired images for different motion ranges show that this method produces a better estimation with respect to the homogeneous (no Gadap t ive) mult iscale met hod.
一种实时运动场估计的自适应多尺度方案
在这项工作中考虑的问题是从图像的时间序列中估计运动场(即速度场在图像平面上的投影)。通用图像包含不同空间频率和运动幅度的不同对象。为了快速有效地处理这种复杂的环境,生物视觉系统采用并行处理、不同分辨率的视觉通道和自适应机制。本文提出了一种新的自适应多尺度方案,该方案的空间离散尺度基于误差的局部估计。考虑到实时性、灵活性和可移植性的限制,该方案可以在中等粒度的MIMD并行计算机上高效实现。对不同运动范围的光线跟踪和视频采集图像进行的测试表明,该方法相对于均匀(无Gadap t - ive)多尺度方法产生了更好的估计。
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