Visual tracking in low frame rate videos has many inherent difficulties for achieving accurate target recovery, such as occlusions, abrupt motions and rapid pose changes. Thus, conventional tracking methods cannot be applied reliably. In this paper, we offer a new scheme for tracking objects in low frame rate videos. We present a method of integrating multiple metrics for template matching, as an extension for the particle filter. By inspecting a large data set of videos for tracking, we show that our method not only outperforms other related benchmarks in the field, but it also achieves better results both visually and quantitatively, once compared to actual ground truth data.
|Title of host publication||Advances in Visual Computing - 10th International Symposium, ISVC 2014, Proceedings|
|Editors||George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Ryan McMahan, Jason Jerald, Hui Zhang, Steven M. Drucker, Kambhamettu Chandra, El Choubassi Maha, Zhigang Deng, Mark Carlson|
|Number of pages||12|
|State||Published - 2014|
|Event||10th International Symposium on Visual Computing, ISVC 2014 - Las Vegas, United States|
Duration: 8 Dec 2014 → 10 Dec 2014
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Conference||10th International Symposium on Visual Computing, ISVC 2014|
|Period||8/12/14 → 10/12/14|
Bibliographical notePublisher Copyright:
© Springer International Publishing Switzerland 2014.