학술논문

TCM: a vision-based algorithm for distinguishing between stationary and moving objects irrespective of depth contrast from a UAS
Document Type
Report
Source
International Journal of Advanced Robotic Systems. May 10, 2016, p1, 17 p.
Subject
Algorithm
Incremental motion control -- Methods
Engineering research
Drone aircraft -- Design and construction
Machine vision -- Research
Algorithms -- Research
Language
English
ISSN
1729-8806
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. Keywords Computer Vision, UAS, Optic Flow, Motion Classification, Moving Object Detection, TCM, Motion Contrast, Background Subtraction, Coplanarity Constraint, Epipolar Plane Constraint
1. Introduction Is it moving or not? In aerial navigation, answering this question can provide manned and unmanned vehicles with situational awareness in a dynamic environment, and the ability to [...]