Open AccessEvent‐based motion segmentation of small objects in the wild
Author(s) -
Sun Zhezheng,
Hou Chuantong,
Wang Longguang,
Deng Xinpu,
Li Miao
Publication year - 2022
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/ell2.12582
Subject(s) - computer vision , artificial intelligence , segmentation , computer science , motion (physics) , event (particle physics) , motion estimation , image segmentation , motion detection , physics , quantum mechanics
Event‐based cameras are sensitive to brightness changes and can capture rich temporal information with very high temporal resolution, which has great potential for motion segmentation of moving objects. Under static background, events are only triggered by motion of objects, thereby moving objects can be easily segmented. However, in many real‐world applications, events are also triggered by the motion of camera or background and submerge the ones corresponding to moving objects. In this letter, an event‐based motion segmentation method to segment moving small objects in events obtained from the wild is proposed. First, motion estimation is performed to align the events triggered by the background. Then, candidate events corresponding to moving objects or moving backgrounds are detected. Finally, motion information is adopted to segment the events of moving small objects from the ones triggered by the background. In addition, the first dataset for event‐based motion segmentation of small objects is developed. Experimental results demonstrate the effectiveness of this method and show that this method can achieve robust motion segmentation of small moving objects in the wild.