DocumentCode :
3748497
Title :
Contour Detection and Characterization for Asynchronous Event Sensors
Author :
Francisco Barranco;Ching L. Teo; Ferm?ller;Yiannis Aloimonos
Author_Institution :
Comput. Vision Lab., Univ. of Maryland, College Park, MD, USA
fYear :
2015
Firstpage :
486
Lastpage :
494
Abstract :
The bio-inspired, asynchronous event-based dynamic vision sensor records temporal changes in the luminance of the scene at high temporal resolution. Since events are only triggered at significant luminance changes, most events occur at the boundary of objects and their parts. The detection of these contours is an essential step for further interpretation of the scene. This paper presents an approach to learn the location of contours and their border ownership using Structured Random Forests on event-based features that encode motion, timing, texture, and spatial orientations. The classifier integrates elegantly information over time by utilizing the classification results previously computed. Finally, the contour detection and boundary assignment are demonstrated in a layer-segmentation of the scene. Experimental results demonstrate good performance in boundary detection and segmentation.
Keywords :
"Image edge detection","Motion segmentation","Voltage control","Computer vision","Image segmentation","Feature extraction","Sensors"
Publisher :
ieee
Conference_Titel :
Computer Vision (ICCV), 2015 IEEE International Conference on
Electronic_ISBN :
2380-7504
Type :
conf
DOI :
10.1109/ICCV.2015.63
Filename :
7410420
Link To Document :
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