Title :
Shape-based pedestrian parsing
Author :
Bo, Yihang ; Fowlkes, Charless C.
Author_Institution :
Sch. of Comput. & Inf. Technol., Beijing Jiaotong Univ., Beijing, China
Abstract :
We describe a simple model for parsing pedestrians based on shape. Our model assembles candidate parts from an oversegmentation of the image and matches them to a library of exemplars. Our matching uses a hierarchical decomposition into a variable number of parts and computes scores on partial matchings in order to prune the search space of candidate segment. Simple constraints enforce consistent layout of parts. Because our model is shape-based, it generalizes well. We use exemplars from a controlled dataset of poses but achieve good test performance on unconstrained images of pedestrians in street scenes. We demonstrate results of parsing detections returned from a standard scanning-window pedestrian detector and use the resulting parse to perform viewpoint prediction and detection re-scoring.
Keywords :
feature extraction; image matching; image segmentation; object detection; detection rescoring; hierarchical decomposition; image matching; image oversegmentation; parsing detection; partial matching; scanning-window pedestrian detector; search space; shape-based pedestrian parsing; street scene; viewpoint prediction; Accuracy; Assembly; Face; Image segmentation; Legged locomotion; Shape;
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on
Conference_Location :
Providence, RI
Print_ISBN :
978-1-4577-0394-2
DOI :
10.1109/CVPR.2011.5995609