Multi-primitive hierarchical (MPH) stereo analysis

This paper develops and demonstrates a new computational framework for an accurate, robust, and efficient stereo approach. In multi-primitive hierarchical (MPH) computational model, stereo analysis is performed in multiple stages, incorporating multiple primitives, utilizing a hierarchical control strategy. The MPH stereo system consists of three integrated subsystems: region-based analysis module; linear edge segment-based analysis module; and edgel-based stereo analysis module. Results of stereo analysis at higher levels of the hierarchy are used for guidance at the lower levels. The MPH stereo system does not overly rely on one type of primitive and therefore will reliably work on a wide range of scenes. The MPH stereo analysis results in the generation of several disparity maps of multiple abstraction. Disparity maps generated at each level can be fused to obtain an accurate and fine resolution disparity map. The MPH approach also provides the capability to selectively analyze image regions with varying detail. This provides the means for adaptively extracting range information of only sufficient resolution. Thus, a stereo system that utilizes primitives of different abstraction and a multilevel hierarchical computational strategy will be superior to a single-level, single-primitive system. Extensive experimentation is carried out on a wide array of scenes of varying complexity from two application domains to systematically evaluate the validity and performance of the MPH framework. The MPH stereo system is able to analyze images in most cases with 85%~100% matching accuracy in under a minute of processing time and yield depth values typically within ±2% of the actual depth