Conference proceeding
Going with the Flow: Pedestrian Efficiency in Crowded Scenes
COMPUTER VISION - ECCV 2012, PT IV, v 7575(4), pp 558-572
01 Jan 2012
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Video analysis of crowded scenes is challenging due to the complex motion of individual people in the scene. The collective motion of pedestrians form a crowd flow, but individuals often largely deviate from it as they anticipate and react to each other. Deviations from the crowd decreases the pedestrian's efficiency: a sociological concept that measures the difference of actual motion from the intended speed and direction. In this paper, we derive a novel method for estimating pedestrian efficiency from videos. We first introduce a novel crowd motion model that encodes the temporal evolution of local motion patterns represented with directional statistics distributions. This model is then used to estimate the intended motion of pedestrians at every space-time location, which enables visual measurement of the pedestrian efficiency. We demonstrate the use of this pedestrian efficiency to detect unusual events and to track individuals in crowded scenes. Experimental results show that the use of pedestrian efficiency leads to state-of-the-art accuracy in these critical applications.
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Details
- Title
- Going with the Flow: Pedestrian Efficiency in Crowded Scenes
- Creators
- Louis Kratz - Drexel UniversityKo Nishino - Drexel University
- Contributors
- A Fitzgibbon (Editor)S Lazebnik (Editor)P Perona (Editor)Y Sato (Editor)C Schmid (Editor)
- Publication Details
- COMPUTER VISION - ECCV 2012, PT IV, v 7575(4), pp 558-572
- Series
- Lecture Notes in Computer Science
- Publisher
- Springer Nature
- Number of pages
- 15
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:000342818800040
- Scopus ID
- 2-s2.0-84867859854
- Other Identifier
- 991019170137504721
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- Web of Science research areas
- Computer Science, Theory & Methods