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Sensors 2013, 13(10), 13685-13707; doi:10.3390/s131013685

Video Sensor-Based Complex Scene Analysis with Granger Causality

1,2,* , 1,2
,
1,2
,
1,2
and
1,2
1
Institution of Image Communication and Information Processing, Department of ElectronicEngineering, Shanghai Jiaotong University, Shanghai 200240, China
2
Shanghai Key Laboratory of Digital Media Processing and Transmission, Shanghai 200240, China
*
Author to whom correspondence should be addressed.
Received: 10 June 2013 / Revised: 10 September 2013 / Accepted: 13 September 2013 / Published: 11 October 2013
(This article belongs to the Section Physical Sensors)
View Full-Text   |   Download PDF [2771 KB, uploaded 21 June 2014]   |  

Abstract

In this report, we propose a novel framework to explore the activity interactions and temporal dependencies between activities in complex video surveillance scenes. Under our framework, a low-level codebook is generated by an adaptive quantization with respect to the activeness criterion. The Hierarchical Dirichlet Processes (HDP) model is then applied to automatically cluster low-level features into atomic activities. Afterwards, the dynamic behaviors of the activities are represented as a multivariate point-process. The pair-wise relationships between activities are explicitly captured by the non-parametric Granger causality analysis, from which the activity interactions and temporal dependencies are discovered. Then, each video clip is labeled by one of the activity interactions. The results of the real-world traffic datasets show that the proposed method can achieve a high quality classification performance. Compared with traditional K-means clustering, a maximum improvement of 19.19% is achieved by using the proposed causal grouping method. View Full-Text
Keywords: video surveillance; scene analysis; topic model; point process; Granger causality video surveillance; scene analysis; topic model; point process; Granger causality
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Fan, Y.; Yang, H.; Zheng, S.; Su, H.; Wu, S. Video Sensor-Based Complex Scene Analysis with Granger Causality. Sensors 2013, 13, 13685-13707.

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