NDLI: New approach of imagery generation and target recognition based on 3D LIDAR data

Content Provider	IEEE Xplore Digital Library
Author	Jinhui Lan Zhuoxun Shen
Copyright Year	2009
Description	Author affiliation: Department of Measurement and Control Technologies, School of Information Engineering, University of Science and Technology Beijing, Beijing 100083, China (Jinhui Lan; Zhuoxun Shen)
Abstract	Light Detection and Ranging (LIDAR) sensor is an advanced technology of 3D-measurement with high accuracy. The processing of 3D point cloud data collected via LIDAR sensor is of topical interest for 3D target recognition. In this paper, a new approach of imagery generation and target recognition based on 3D LIDAR data is presented. The raw 3D point cloud data are transformed and interpolated to be stored in 2D matrix. The target imagery is generated and visualized by means of height-gray mapping principle proposed in paper. For different poses of target, the affine invariable moments of target imagery are selected as features for recognition because of its invariance in rotation, scaling, translation and affine transformation. BP neural network algorithm and Support Vector Machine (SVM) algorithm are utilized as method of target classification and recognition. The recognition results by two algorithms are compared against and analyzed detailedly. The new method had been applied into target recognition in outdoor experiments. Different types of targets are classified and the rate of correct recognition is greater than 95%. Through outdoor experiments, it can be proven that this new method is applied to the field of 3D target recognition effectively and stability.
File Size	182098
File Format	PDF
ISBN	9781424438631
DOI	10.1109/ICEMI.2009.5274790
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-08-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Image recognition Target recognition imagery generation Clouds 3D point cloud target recognition Support vector machines Laser radar Neural networks affine invariable moment Support vector machine classification Data visualization Image generation LIDAR sensor
Content Type	Text
Resource Type	Article

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