TCM: a vision-based algorithm for distinguishing between stationary and moving objects irrespective of depth contrast from a UAS

Strydom, Reuben, Thurrowgood, Saul, Denuelle, Aymeric and Srinivasan, Mandyam V. (2016) TCM: a vision-based algorithm for distinguishing between stationary and moving objects irrespective of depth contrast from a UAS. International Journal of Advanced Robotic Systems, 13 84: . doi:10.5772/62846


Author Strydom, Reuben
Thurrowgood, Saul
Denuelle, Aymeric
Srinivasan, Mandyam V.
Title TCM: a vision-based algorithm for distinguishing between stationary and moving objects irrespective of depth contrast from a UAS
Journal name International Journal of Advanced Robotic Systems   Check publisher's open access policy
ISSN 1729-8806
1729-8814
Publication date 2016-05-10
Year available 2016
Sub-type Article (original research)
DOI 10.5772/62846
Open Access Status DOI
Volume 13
Issue 84
Total pages 17
Place of publication Rijeka, Croatia
Publisher InTech Open Access Publisher
Collection year 2017
Language eng
Abstract This paper describes an airborne vision system that is capable of determining whether an object is moving or stationary in an outdoor environment. The proposed method, coined the Triangle Closure Method (TCM), achieves this goal by computing the aircraft's egomotion and combining it with information about the directions connecting the object and the UAS, and the expansion of the object in the image. TCM discriminates between stationary and moving objects with an accuracy rate of up to 96%. The performance of the method is validated in outdoor field tests by implementation in real-time on a quadrotor UAS. We demonstrate that the performance of TCM is better than that of a traditional background subtraction technique, as well as a method that employs the Epipolar Constraint Method. Unlike background subtraction, TCM does not generate false alarms due to parallax when a stationary object is at a distance other than that of the background. It also prevents false negatives when the object is moving along an epipolar constraint. TCM is a reliable and computationally efficient scheme for detecting moving objects, which provides an additional safety layer for autonomous navigation.
Keyword Computer vision
UAS
Optic flow
Motion classification
Moving object detection
Triangle closure method
TCM
Motion contrast
Background subtraction
Coplanarity constraint
Epipolar plane constraint
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
Queensland Brain Institute Publications
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