详情

原文传递 ILLUMINATION INVARIANT AND OCCLUSION ROBUST VEHICLE TRACKING BY SPATIO-TEMPORAL MRF MODEL.

题名：	ILLUMINATION INVARIANT AND OCCLUSION ROBUST VEHICLE TRACKING BY SPATIO-TEMPORAL MRF MODEL.
作者：	Kamijo-S; Sakauchi-M
关键词：	Correlation-analysis; Energy-; Illuminating-engineering; Markov-processes; Tracking-systems; Variational-inequalities-Mathematics; Vehicles-
摘要：	For many years, vehicle tracking of images has suffered from the problems of occlusions and sudden variations in illumination. In order to resolve these occlusion problems, we have been proposing the Spatio-Temporal Markov Random Field model (S-T MRF) for segmentation of spatio-temporal images. This S-T MRF optimizes the segmentation boundaries of occluded vehicles and their motion vectors simultaneously, by referring to textures and segment labeling correlations along the temporal axis, as well as the spatial axes. Consequently, S-T MRF has been proven to be successful for vehicle tracking even against severe occlusions found in low-angle images with complicated motions, such at highway junctions. Furthermore in this paper, a method to obtain the illumination invariant images by estimating MRF energy among neighbor pixel intensities is described. These illumination invariant images are very stable even when sudden variations in illumination are caused by such as clouds hiding sunshine in the original images. Thus, vehicle tracking was performed successfully even against sudden variations in illumination or shading effects. In addition, we succeeded in seamlessly integrating the method for MRF energy images into our S-T MRF model. In this paper, the idea of the integrated S-T MRF model and successful results of vehicle tracking against sudden variations in illumination as well as occlusions will be described in detail.
总页数：	Conference Title: 9th World Congress on Intelligent Transport Systems. Location: Chicago, Illinois. Sponsored by: ITS America, ITS Japan, ERTICO (Intelligent Transport Systems and Services-Europe). Held: 20021014-20021017. 2002. pp12
报告类型：	科技报告