Optical flow from 1-D correlation: Application to a simple time-to-crash detector
作者:Nicola Ancona, Tomaso Poggio
摘要
In the first part of this article we show that a new technique exploiting 1-D correlation of 2-D or even 1-D patches between successive frames may be sufficient to compute a satisfactory estimation of the optical flow field. The algorithm is well suited to VLSI implementations. The sparse measurements provided by the technique can be used to compute qualitative properties of the flow for a number of different visual tasks. In particular, the second part of the article shows how to combine our 1-D correlation technique with a scheme for detecting expansion or rotation (Poggio et al. 1991) in a simple algorithm which also suggests interesting biological implications. The algorithm provides a rough estimate of time-to-crash. It was tested on real-image sequences. We show its performance and compare the results to previous approaches.
论文关键词:Image Processing, Artificial Intelligence, Flow Field, Computer Vision, Computer Image
论文评审过程:
论文官网地址:https://doi.org/10.1007/BF01418979