Hierarchical spatiotemporal modeling for dynamic video trajectory analysis

Byung Hyung Kim; Hak Chul Shin; Phill Kyu Rhee

doi:10.1117/1.3641416

1 October 2011 Hierarchical spatiotemporal modeling for dynamic video trajectory analysis

Byung Hyung Kim, Hak Chul Shin, Phill Kyu Rhee

Author Affiliations +

Optical Engineering, Vol. 50, Issue 10, 107206 (October 2011). https://doi.org/10.1117/1.3641416

Abstract

Normalcy decision in video security involves highly uncertain phenomena due to its inherited insufficient knowledge, intrinsic ambiguity in human cognition, measurement error, etc. This paper presents a hierarchical spatiotemporal trajectory modeling for dynamic trajectory analysis using sparse trajectory data. The trajectory data is assumed to be given by people detection and tracking methods, which are also challenging issues due to occlusion, noise, illumination changes, etc. The proposed method partitions the trajectory feature space into the attributes of trajectory position, direction, and speed. Inherent uncertainty of video trajectory is tackled by employing the uncertainty propagation model of a trajectory segment and Markov random field in analyzing the uncertainty attributes of object movement direction and speed. The proposed method can be used in online learning for incremental adaptation as well as offline learning for optimality guarantee. The method was evaluated using both synthetic trajectories and video streams of multiple people movements acquired from multiple video cameras developed by GE Global Research Center and KAL beta sites. Extensive experiments were performed using video sequences in real world and synthesized trajectories, which achieved very encouraging results.

©(2011) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Byung Hyung Kim, Hak Chul Shin, and Phill Kyu Rhee "Hierarchical spatiotemporal modeling for dynamic video trajectory analysis," Optical Engineering 50(10), 107206 (1 October 2011). https://doi.org/10.1117/1.3641416

Published: 1 October 2011

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available