TY - GEN
T1 - A modified KLT multiple objects tracking framework based on global segmentation and adaptive template
AU - Xue, Kang
AU - Vela, Patricio A.
AU - Liu, Yue
AU - Wang, Yongtian
PY - 2012
Y1 - 2012
N2 - This paper presents a modified Kanade-Lucas-Tomasi (KLT) tracking framework for multiple objects tracking applications. First, the framework includes a global pixel-level probabilistic model and an adaptive RGB template model to modify traditional KLT tracker more robust to track multiple objects and partial occlusions. Meanwhile, a Merge and Split algorithm is introduced in the proposed framework to track complete occlusions. The advantage of our method is demonstrated on a variety of challenging video sequences.1
AB - This paper presents a modified Kanade-Lucas-Tomasi (KLT) tracking framework for multiple objects tracking applications. First, the framework includes a global pixel-level probabilistic model and an adaptive RGB template model to modify traditional KLT tracker more robust to track multiple objects and partial occlusions. Meanwhile, a Merge and Split algorithm is introduced in the proposed framework to track complete occlusions. The advantage of our method is demonstrated on a variety of challenging video sequences.1
UR - http://www.scopus.com/inward/record.url?scp=84874576098&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84874576098
SN - 9784990644109
T3 - Proceedings - International Conference on Pattern Recognition
SP - 3561
EP - 3564
BT - ICPR 2012 - 21st International Conference on Pattern Recognition
T2 - 21st International Conference on Pattern Recognition, ICPR 2012
Y2 - 11 November 2012 through 15 November 2012
ER -