Invariant unsupervised segmentation of dismounts in depth images
Nathan S. Butler, Richard L. Tutwiler · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
This paper will describe a scene invariant method for the unsupervised segmentation of dismounts in depth images. This method can be broken into two parts: ground plane detection and spatial segmentation. The former is accomplished by using RANSAC (RANdom SAmple Consensus) to identify a ground plane in the scene. After performing contrast enhancement the Image is "sliced" into regions. Each classified region is processed by a Robert's edge detector in order to separate each object. Each output is further processed by a block of shape filters that extract the human form.