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| Frédéric Jurie, Michel Dhome, "Hyperplane Approximation for Template Matching," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp. 996-1000, July, 2002. | |||
| BibTex | x | ||
| @article{ 10.1109/TPAMI.2002.1017625, author = {Frédéric Jurie and Michel Dhome}, title = {Hyperplane Approximation for Template Matching}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {24}, number = {7}, issn = {0162-8828}, year = {2002}, pages = {996-1000}, doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2002.1017625}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - Hyperplane Approximation for Template Matching IS - 7 SN - 0162-8828 SP996 EP1000 EPD - 996-1000 A1 - Frédéric Jurie, A1 - Michel Dhome, PY - 2002 KW - Visual tracking KW - motion estimation. VL - 24 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
Hager and Belhumeur recently proposed a general framework for object tracking in video images. It consists of low-order parametric models for the image motion of a target region. These models are used to predict movement and to track the target. The difference in intensity between the pixels belonging to the current region and the pixels of the selected target (learned during an offline stage) allows a straightforward prediction of the region position in the current image. The main aim of this article is to propose an important improvement within this framework, making the convergence faster with the same amount of online computation.
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