Towards Detecting People Carrying Objects - A Periodicity Dependency Pattern Approach.
作者： Volker Eiselein , Rubén Heras Evangelio , Michael Pätzold , Tobias Senst , Thomas Sikora
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摘要: … Since we are using short video … Therefore we define the periodicity dependency (PD) of two blocks as the maximum of the absolute relative correlation of the similarity plot. The PD of a …
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tu-berlin.de 参考文章(9)
Thanarat Horprasert, David Harwood, Larry S Davis, None, A Robust Background Subtraction and Shadow Detection ,(1999)
Murat Ekinci, Murat Aykut, Human Gait Recognition Based on Kernel PCA Using Projections Journal of Computer Science and Technology. ,vol. 22, pp. 867- 876 ,(2007) , 10.1007/S11390-007-9101-Z
David Webb, Russell H. Tuttle, Michael Baksh, Pendular activity of human upper limbs during slow and normal walking American Journal of Physical Anthropology. ,vol. 93, pp. 477- 489 ,(1994) , 10.1002/AJPA.1330930407
Ismail Haritaoglu, Ross Cutler, David Harwood, Larry S. Davis, Backpack: detection of people carrying objects using silhouettes Computer Vision and Image Understanding. ,vol. 81, pp. 385- 397 ,(2001) , 10.1006/CVIU.2000.0893
C. Stauffer, W.E.L. Grimson, Adaptive background mixture models for real-time tracking computer vision and pattern recognition. ,vol. 2, pp. 246- 252 ,(1999) , 10.1109/CVPR.1999.784637
S.S. Pathan, A. Al-Hamadi, T. Senst, B. Michaelis, Multi-object tracking using semantic analysis and Kalman filter international symposium on image and signal processing and analysis. pp. 271- 276 ,(2009) , 10.1109/ISPA.2009.5297722
I. Haritaoglu, D. Harwood, L.S. Davis, W/sup 4/: real-time surveillance of people and their activities IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 22, pp. 809- 830 ,(2000) , 10.1109/34.868683
Dima Damen, David Hogg, Detecting Carried Objects in Short Video Sequences Lecture Notes in Computer Science. pp. 154- 167 ,(2008) , 10.1007/978-3-540-88690-7_12
C. BenAbdelkader, L. Davis, Detection of people carrying objects : a motion-based recognition approach ieee international conference on automatic face and gesture recognition. pp. 378- 383 ,(2002) , 10.1109/AFGR.2002.1004183