Title :
A rotation invariant and realtime online template matching method for object detection
Author_Institution :
Inf. & Sci. Technol. Inst., Peking Univ., Shenzhen, China
Abstract :
This paper propose an object recognition method based on template match that uses both gradient and LBP feature as the template feature. We also design a binary representation and quick bitwise operation for the proposed approach.
Keywords :
feature extraction; image matching; image representation; object detection; LBP feature; binary representation; bitwise operation; gradient feature; local binary pattern feature; object detection; object recognition method; rotation invariant template matching; Boosting; Feature extraction; Histograms; Humans; Object detection; Real time systems; Robustness; LBP; online learning; rotation invariance; template feature;
Conference_Titel :
Consumer Electronics, Communications and Networks (CECNet), 2011 International Conference on
Conference_Location :
XianNing
Print_ISBN :
978-1-61284-458-9
DOI :
10.1109/CECNET.2011.5768198
