Clustering of laser measurements via the Dirichlet process mixture model for object tracking

Yung Chou Lee*, Te-Sheng Hsiao, Chih Tang Chang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, the Dirichlet process mixture model is used to describe the distribution of the whole laser measurements in a given scan. Then the number of clusters is inferred from the measurements by the Gibbs sampler. We focus on the automotive application which usually has a more complex environment. Due to the variant shapes and sizes of the real traffic objects, the multi-class DP-based clustering model, which is incorporated with a mixture prior distribution, is proposed to cluster the measurements more properly. The clustering results of the proposed method are compared with those of several existing clustering methods both in an expressway case and in an urban road case. The corresponding tracking performances are also analyzed and the improvements of the proposed method are presented.

Original languageEnglish
Title of host publicationAIM 2012 - 2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Conference Digest
Pages837-842
Number of pages6
DOIs
StatePublished - 5 Oct 2012
Event2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2012 - Kaohsiung, Taiwan
Duration: 11 Jul 201214 Jul 2012

Publication series

NameIEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM

Conference

Conference2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2012
CountryTaiwan
CityKaohsiung
Period11/07/1214/07/12

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    Lee, Y. C., Hsiao, T-S., & Chang, C. T. (2012). Clustering of laser measurements via the Dirichlet process mixture model for object tracking. In AIM 2012 - 2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Conference Digest (pp. 837-842). [6265917] (IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM). https://doi.org/10.1109/AIM.2012.6265917