Abstract
Multiple object tracking is a field with extensive practical applications. The problem of multiple object tracking can be broken down to tracking and association. The algorithms of common tracking and association algorithms are described in this paper and their relative characteristics described. Two different association algorithms, Global Nearest Neighbor and Multiple Hypothesis Tracking are compared using a MATLAB simulation run on different test footage. The characteristic features with regards to track creation and assignment accuracy of the two are shown by their performance in both cases.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
