Tracking People in Dense Crowds Using Supervoxels

Shota Takayama; Teppei Suzuki; Yoshimitsu Aoki; Sho Isobe; Makoto Masuda

doi:10.1109/SITIS.2016.90

Tracking People in Dense Crowds Using Supervoxels

Shota Takayama, Teppei Suzuki, Yoshimitsu Aoki, Sho Isobe, Makoto Masuda

Department of Electronics and Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The demand for people tracking in dense crowds is increasing, but it is a challenging problem in the computer vision field. 'Crowd tracking' is extremely difficult because of hard occlusions, various motions and posture changes. In particular, we need to handle occlusions for more robust tracking. This paper discusses robust crowd tracking based on a combination of supervoxels and optical flow tracking. The SLIC based supervoxel algorithm adaptively estimates the boundary between a person and a background. Therefore, the combination of supervoxels and optical flow tracking becomes a highly reliable approach for crowd tracking. In tracking experiments, high performance is achieved for the UCF crowd dataset.

Original language	English
Title of host publication	Proceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	532-537
Number of pages	6
ISBN (Electronic)	9781509056989
DOIs	https://doi.org/10.1109/SITIS.2016.90
Publication status	Published - 2017 Apr 21
Event	12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016 - Naples, Italy Duration: 2016 Nov 28 → 2016 Dec 1

Other

Other	12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016
Country/Territory	Italy
City	Naples
Period	16/11/28 → 16/12/1

Keywords

dense crowd
optical flow
People tracking
supervoxel

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Radiology Nuclear Medicine and imaging
Computer Networks and Communications
Signal Processing

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10.1109/SITIS.2016.90

Cite this

Tracking People in Dense Crowds Using Supervoxels. / Takayama, Shota; Suzuki, Teppei; Aoki, Yoshimitsu et al.
Proceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 532-537 7907517.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Takayama, S, Suzuki, T, Aoki, Y, Isobe, S & Masuda, M 2017, Tracking People in Dense Crowds Using Supervoxels. in Proceedings - 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016., 7907517, Institute of Electrical and Electronics Engineers Inc., pp. 532-537, 12th International Conference on Signal Image Technology and Internet-Based Systems, SITIS 2016, Naples, Italy, 16/11/28. https://doi.org/10.1109/SITIS.2016.90

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abstract = "The demand for people tracking in dense crowds is increasing, but it is a challenging problem in the computer vision field. 'Crowd tracking' is extremely difficult because of hard occlusions, various motions and posture changes. In particular, we need to handle occlusions for more robust tracking. This paper discusses robust crowd tracking based on a combination of supervoxels and optical flow tracking. The SLIC based supervoxel algorithm adaptively estimates the boundary between a person and a background. Therefore, the combination of supervoxels and optical flow tracking becomes a highly reliable approach for crowd tracking. In tracking experiments, high performance is achieved for the UCF crowd dataset.",

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Tracking People in Dense Crowds Using Supervoxels

Abstract

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Keywords

ASJC Scopus subject areas

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