Abstract
A novel real-time object tracking algorithm is proposed which tracks objects in real-time on an iPhone platform. The system utilizes information such as image intensity, color, edges, and texture for matching different candidate tracks. The tracking system adapts to changes in target appearance and size (including resizing candidate tracks to a universal depth-independent size) while running at 10-15FPS tracking rate. Several experiments conducted on actual video are used to illustrate the proposed approach. © 2011 Springer-Verlag.
Cite
CITATION STYLE
Heidari, A., & Aarabi, P. (2011). Real-time object tracking on iPhone. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6938 LNCS, pp. 768–777). https://doi.org/10.1007/978-3-642-24028-7_71
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