Minimum Delay Moving Object Detection

Handle URI:
http://hdl.handle.net/10754/623383
Title:
Minimum Delay Moving Object Detection
Authors:
Lao, Dong ( 0000-0001-9308-7085 ) ; Sundaramoorthi, Ganesh ( 0000-0003-3471-6384 )
Abstract:
We present a general framework and method for detection of an object in a video based on apparent motion. The object moves relative to background motion at some unknown time in the video, and the goal is to detect and segment the object as soon it moves in an online manner. Due to unreliability of motion between frames, more than two frames are needed to reliably detect the object. Our method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Conference/Event name:
Winter Enrichment Program 2017 - Poster Competition
Issue Date:
8-Jan-2017
Type:
Poster
Appears in Collections:
Posters; Winter Enrichment Program 2017

Full metadata record

DC FieldValue Language
dc.contributor.authorLao, Dongen
dc.contributor.authorSundaramoorthi, Ganeshen
dc.date.accessioned2017-05-07T05:48:00Z-
dc.date.available2017-05-07T05:48:00Z-
dc.date.issued2017-01-08-
dc.identifier.urihttp://hdl.handle.net/10754/623383-
dc.description.abstractWe present a general framework and method for detection of an object in a video based on apparent motion. The object moves relative to background motion at some unknown time in the video, and the goal is to detect and segment the object as soon it moves in an online manner. Due to unreliability of motion between frames, more than two frames are needed to reliably detect the object. Our method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.en
dc.titleMinimum Delay Moving Object Detectionen
dc.typePosteren
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.conference.dateJanuary 8-21 2017en
dc.conference.nameWinter Enrichment Program 2017 - Poster Competitionen
dc.conference.locationKAUSTen
kaust.authorLao, Dongen
kaust.authorSundaramoorthi, Ganeshen
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