By Topic

Tracking objects of arbitrary shape using expectation-maximization algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Shuqing Zeng ; R&D, Electr. & Controls Integration Lab., Gen. Motors, Warren, MI, USA ; Yuanhong Li ; Yantao Shen

We address the general object tracking with arbitrary shape using rangefinders, which is a key module for detecting surrounding traffic and infrastructure for an autonomous driving vehicle. An Expectation-Maximization (EM) algorithm with locally matching is proposed for motion estimation between two consecutive range images. The complexity of the algorithm is O(N) with N the numbers of scan points. Quantitative performance evaluation of the algorithm using a benchmarking vehicular data set. Results of road tests show the effectiveness and efficiency of the implemented system.

Published in:

Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on

Date of Conference:

25-30 Sept. 2011