BAYESIAN VEHICLE CLASS RECOGNITION USING 3-D PROBE

被引：2
|
作者：
Han, D. [1 ]
Cooper, D. B. [2 ]
Hahn, H. -S. [1 ]
机构：
[1] Soongsil Univ, Intelligent Robot Res Ctr, Seoul 156743, South Korea
[2] Brown Univ, Providence, RI 02912 USA
来源：
INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY | 2013年 / 14卷 / 05期
关键词：
Vehicle class recognition; Probe; MAP (Maximum A Posteri) estimation; Bayesian recognition; CLASSIFICATION; REPRESENTATION;
D O I：
10.1007/s12239-013-0082-3
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
A new approach is presented to vehicle-class recognition from video clips. Two new concepts introduced are: probes consisting of local 3-d curve-groups which when projected into video frames are features for recognizing vehicle classes in video clips; and Bayesian recognition based on class probability densities for groups of 3-d distances between pairs of 3-d probes. A full Bayesian recognizer is realized via Monte Carlo simulation method. Also, a sub-optimal but robust camera calibration method is employed and tested extensively.
引用
收藏
页码：747 / 756
页数：10
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