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TASK-DEPENDENT SALIENCY ESTIMATION FROM TRAJECTORIES OF AGENTS IN VIDEO SEQUENCES

Abstract: 

This paper proposes a method for detecting zones of visual attention based on the motion of agents in a video analytics
context. By considering a Hough transform approach, linear flow motions are grouped based on attractive salient zones where they converge. Each group of linear flows is generalized through the whole environment by using a nonparametric stochastic approach that can be used to generate a map that illustrates the effects that each zone exerts on the dynamics of agents. A dataset of walking pedestrians and trajectories generated by a robot that executes a single task in a close environment are used to validate the proposed method.

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Paper Details

Authors:
Mohamad Baydoun
Submitted On:
8 October 2018 - 7:48am
Short Link:
Type:
Poster
Event:

Document Files

ICIP2017.pdf

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[1] Mohamad Baydoun, "TASK-DEPENDENT SALIENCY ESTIMATION FROM TRAJECTORIES OF AGENTS IN VIDEO SEQUENCES", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/2020. Accessed: Oct. 24, 2020.
@article{2020-17,
url = {http://sigport.org/2020},
author = {Mohamad Baydoun },
publisher = {IEEE SigPort},
title = {TASK-DEPENDENT SALIENCY ESTIMATION FROM TRAJECTORIES OF AGENTS IN VIDEO SEQUENCES},
year = {2017} }
TY - EJOUR
T1 - TASK-DEPENDENT SALIENCY ESTIMATION FROM TRAJECTORIES OF AGENTS IN VIDEO SEQUENCES
AU - Mohamad Baydoun
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/2020
ER -
Mohamad Baydoun. (2017). TASK-DEPENDENT SALIENCY ESTIMATION FROM TRAJECTORIES OF AGENTS IN VIDEO SEQUENCES. IEEE SigPort. http://sigport.org/2020
Mohamad Baydoun, 2017. TASK-DEPENDENT SALIENCY ESTIMATION FROM TRAJECTORIES OF AGENTS IN VIDEO SEQUENCES. Available at: http://sigport.org/2020.
Mohamad Baydoun. (2017). "TASK-DEPENDENT SALIENCY ESTIMATION FROM TRAJECTORIES OF AGENTS IN VIDEO SEQUENCES." Web.
1. Mohamad Baydoun. TASK-DEPENDENT SALIENCY ESTIMATION FROM TRAJECTORIES OF AGENTS IN VIDEO SEQUENCES [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/2020