NDLI: Spatio-temporal motion features for laser-based moving objects detection and tracking

Content Provider	IEEE Xplore Digital Library
Author	Xiaotong Shen Seong-Woo Kim Ang, M.H.
Copyright Year	2014
Description	Author affiliation: Singapore-MIT Alliance for Res. & Technol., Singapore, Singapore (Seong-Woo Kim) \|\| Nat. Univ. of Singapore, Singapore, Singapore (Xiaotong Shen; Ang, M.H.)
Abstract	This paper proposes a spatio-temporal motion feature detection and tracking method using range sensors working on a moving platform. The proposed spatio-temporal motion features are similar to optical flow but are extended on a moving platform with fusion of odometry and show much better classification accuracy with consideration of different uncertainties. In the proposal, the ego motion is compensated by odometry sensors and the laser scan points are accumulated and represented as space-time point clouds, from which the velocities and moving directions can be extracted. Based on these spatio-temporal features, a supervised learning technique is applied to classify the points as static or moving and Kalman filters are implemented to track the moving objects. A real experiment is performed during day and night on an autonomous vehicle platform and shows promising results in a crowded and dynamic environment.
Starting Page	4253
Ending Page	4259
File Size	4910008
Page Count	7
File Format	PDF
e-ISBN	9781479969340
DOI	10.1109/IROS.2014.6943162
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sensors Three-dimensional displays Feature extraction Uncertainty Laser radar Motion detection Tracking
Content Type	Text
Resource Type	Article

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