Image gradient evolution - a visual cue for danger
Hongche Liu, Tsai-Hong Hong, Martin Herman, Rama Chellappa · 1995
This paper is concerned with the task of visual motion-based navigation.A critical requirement of the task is the ability to estimate 3-D depth and motion from visual information.Recent studies have demonstrated that the relevant cues is contained in motion parallax or optical flow and that flow field divergence and hence time-to-contact can be extracted.We present a new concept called image gradient evolution (IGE), which utilizes the change of image spatial gradients over time as a threat cue: an approaching object induces 2-D expanding motion and causes the image spatial structure to stretch so the image gradients decrease.Based on this idea, our method offers a one-step solution directly from image gradients,instead offrom optical flow and its derived properties.We use a technique that is local and linear so the implementation can be very fast.The threat map is expectedly noisy but sufficiently informative, as is seen in demonstrations on several real images.These two aspects, fast implementation and useful qualitative information, provide a viable solution to navigational tasks.