Title

A Streakline Representation Of Flow In Crowded Scenes

Abstract

Based on the Lagrangian framework for fluid dynamics, a streakline representation of flow is presented to solve computer vision problems involving crowd and traffic flow. Streaklines are traced in a fluid flow by injecting color material, such as smoke or dye, which is transported with the flow and used for visualization. In the context of computer vision, streaklines may be used in a similar way to transport information about a scene, and they are obtained by repeatedly initializing a fixed grid of particles at each frame, then moving both current and past particles using optical flow. Streaklines are the locus of points that connect particles which originated from the same initial position. In this paper, a streakline technique is developed to compute several important aspects of a scene, such as flow and potential functions using the Helmholtz decomposition theorem. This leads to a representation of the flow that more accurately recognizes spatial and temporal changes in the scene, compared with other commonly used flow representations. Applications of the technique to segmentation and behavior analysis provide comparison to previously employed techniques, showing that the streakline method outperforms the state-of-the-art in segmentation, and opening a new domain of application for crowd analysis based on potentials. © 2010 Springer-Verlag.

Publication Date

1-1-2010

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

6313 LNCS

Issue

PART 3

Number of Pages

439-452

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-642-15558-1_32

Socpus ID

78149329864 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/78149329864

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