Multimodal Stereo Image Registration for Pedestrian Detection
Stephen J. Krotosky, Mohan Manubhai Trivedi · 2006
This paper presents an approach for the registration of multimodal imagery for pedestrian detection when the significant depth differences of objects in the scene preclude a global alignment assumption. Using maximization-of-mutual-information matching techniques and sliding correspondence windows over calibrated image pairs, we demonstrate successful registration of color and thermal data. We develop a robust method using disparity voting for determining the registration of each object in the scene and provide a statistically based measure for evaluating the match confidence. Testing shows successful registration in complex scenes with multiple people at different depths and levels of occlusion