Scene parsing using graph matching on street-view data

作者：Yu Tianshu^*; Wang Ruisheng

来源：Computer Vision and Image Understanding, 2016, 145: 70-80.

DOI：10.1016/j.cviu.2016.01.004

• Scene parsing
• Graph matching
• Markov random field
• Street view

Scene parsing, using both images and range data, is one of the key problems in computer vision and robotics. In this paper, a street scene parsing scheme that takes advantages of images from perspective cameras and range data from LiDAR is presented. First, pre-processing on the image set is performed and the corresponding point cloud is segmented according to semantics and transformed into an image pose. A graph matching approach is introduced into our parsing framework, in order to identify similar sub-regions from training and test images in terms of both local appearance and spatial structure. By using the sub-graphs inherited from training images, as well as the cues obtained from point clouds, this approach can effectively interpret the street scene via a guided MRF inference. Experimental results show a promising performance of our approach.

• 出版日期2016-4