short-paper

3D Person Tracking In World Coordinates and Attribute Estimation with PDR

Authors:

Daisuke Kamisaka,

Naoya Makibuchi,

Shigeyuki SakazawaAuthors Info & Claims

MM '15: Proceedings of the 23rd ACM international conference on Multimedia

Pages 1139 - 1142

https://doi.org/10.1145/2733373.2806301

Published: 13 October 2015 Publication History

Abstract

In this paper, we propose an online 3D person tracking method and an attribute estimation method with pedestrian dead reckoning (PDR). For person tracking, we employ a structured prediction approach, which extends the Struck algorithm. Although the main stream of visual object tracking, including Struck, utilizes only 2D information in image coordinates, it is difficult to track object correctly because of changes in the scale and angle of the target. In contrast, our classifier adaptively learns structural relationship in world coordinates and in image coordinates using Structured SVM. Furthermore, we combine visual tracking results and sensor trajectories based on PDR. Our method estimates a person attribute whether insider like a sales staff, or outsider like a customer. According to experimental results, the proposed method outperforms the existing methods regarding the quality of localization. In addition, experimental results show that our method can estimate the attribute at a ratio of 0.84.

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Cited By

NISHIMURA HMAKIBUCHI NTASAKA KKAWANISHI YMURASE H(2020)Multiple Human Tracking Using an Omnidirectional Camera with Local Rectification and World Coordinates RepresentationIEICE Transactions on Information and Systems10.1587/transinf.2019MVP0009E103.D:6(1265-1275)Online publication date: 1-Jun-2020
https://doi.org/10.1587/transinf.2019MVP0009
Duan WYang TLi JZhang Y(2016)Multiple Pedestrian Tracking Based on Multi-layer Graph with Tracklet Segmentation and MergingBiometric Recognition10.1007/978-3-319-46654-5_80(728-735)Online publication date: 21-Sep-2016
https://doi.org/10.1007/978-3-319-46654-5_80

Index Terms

3D Person Tracking In World Coordinates and Attribute Estimation with PDR
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Tracking
      2. Computer vision tasks
        Scene understanding

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Information

Published In

cover image ACM Conferences

MM '15: Proceedings of the 23rd ACM international conference on Multimedia

October 2015

1402 pages

ISBN:9781450334594

DOI:10.1145/2733373

General Chairs:
Xiaofang Zhou
The University of Queensland, Australia
,
Alan F. Smeaton
Dublin City University, Ireland
,
Qi Tian
The University of Texas at San Antonio, USA
,
Program Chairs:
Dick C.A. Bulterman
FXPAL, USA
,
Heng Tao Shen
The University of Queensland, Australia
,
Ketan Mayer-Patel
The University of North Carolina, USA
,
Shuicheng Yan
National University of Singapore, Singapore

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 October 2015

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MM '15: ACM Multimedia Conference

October 26 - 30, 2015

Brisbane, Australia

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MM '15 Paper Acceptance Rate 56 of 252 submissions, 22%;

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

NISHIMURA HMAKIBUCHI NTASAKA KKAWANISHI YMURASE H(2020)Multiple Human Tracking Using an Omnidirectional Camera with Local Rectification and World Coordinates RepresentationIEICE Transactions on Information and Systems10.1587/transinf.2019MVP0009E103.D:6(1265-1275)Online publication date: 1-Jun-2020
https://doi.org/10.1587/transinf.2019MVP0009
Duan WYang TLi JZhang Y(2016)Multiple Pedestrian Tracking Based on Multi-layer Graph with Tracklet Segmentation and MergingBiometric Recognition10.1007/978-3-319-46654-5_80(728-735)Online publication date: 21-Sep-2016
https://doi.org/10.1007/978-3-319-46654-5_80

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