Histogram of Oriented Displacements (HOD): Describing Trajectories of Human Joints for Action Recognition. Gowayyed, M. A., Torki, M., Hussein, M. E., & El-Saban, M. In Twenty-Third International Joint Conference on Artificial Intelligence, 2013.
Histogram of Oriented Displacements (HOD): Describing Trajectories of Human Joints for Action Recognition [link]Paper  abstract   bibtex   
Creating descriptors for trajectories has many applications in robotics/human motion analysis and video copy detection. Here, we propose a novel descriptor for 2D trajectories: Histogram of Oriented Displacements (HOD). Each displacement in the trajectory votes with its length in a histogram of orientation angles. 3D trajectories are described by the HOD of their three projections. We use HOD to describe the 3D trajectories of body joints to recognize human actions, which is a challenging machine vision task, with applications in human-robot/machine interaction, interactive entertainment, multimedia information retrieval, and surveillance. The descriptor is fixed-length, scale-invariant and speed-invariant. Experiments on MSR-Action3D and HDM05 datasets show that the descriptor outperforms the state-of-the-art when using off-the-shelf classification tools.
@inproceedings{gowayyed_histogram_2013,
	title = {Histogram of Oriented Displacements ({HOD}): Describing Trajectories of Human Joints for Action Recognition},
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	url = {https://www.aaai.org/ocs/index.php/IJCAI/IJCAI13/paper/view/6967},
	shorttitle = {Histogram of Oriented Displacements ({HOD})},
	abstract = {Creating descriptors for trajectories has many applications in robotics/human motion analysis and video copy detection. Here, we propose a novel descriptor for 2D trajectories: Histogram of Oriented Displacements ({HOD}). Each displacement in the trajectory votes with its length in a histogram of orientation angles. 3D trajectories are described by the {HOD} of their three projections. We use {HOD} to describe the 3D trajectories of body joints to recognize human actions, which is a challenging machine vision task, with applications in human-robot/machine interaction, interactive entertainment, multimedia information retrieval, and surveillance. The descriptor is fixed-length, scale-invariant and speed-invariant. Experiments on {MSR}-Action3D and {HDM}05 datasets show that the descriptor outperforms the state-of-the-art when using off-the-shelf classification tools.},
	eventtitle = {Twenty-Third International Joint Conference on Artificial Intelligence},
	booktitle = {Twenty-Third International Joint Conference on Artificial Intelligence},
	author = {Gowayyed, Mohammad Abdelaziz and Torki, Marwan and Hussein, Mohammed Elsayed and El-Saban, Motaz},
	urldate = {2019-05-01},
	date = {2013-06-30},
	year = {2013},
	langid = {english},
	file = {Full Text PDF:C\:\\Users\\Mohamed Hussein\\Zotero\\storage\\IVA94IWX\\Gowayyed et al. - 2013 - Histogram of Oriented Displacements (HOD) Describ.pdf:application/pdf;Snapshot:C\:\\Users\\Mohamed Hussein\\Zotero\\storage\\RB84LZY4\\6967.html:text/html}
}

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