Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/2967413.2974035acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicdscConference Proceedingsconference-collections
short-paper

Tracking multi-object using tracklet and Faster R-CNN: PhD Forum

Published: 12 September 2016 Publication History
  • Get Citation Alerts
  • Abstract

    In this work, we propose an original approach for tracking using tracklets (mini-trajectories) and Faster R-CNN. In fact, the major tracking problem is how an object can keep the same ID during the entire trajectory. To solve problems of tracking, we proceed on the one hand by the definition of a specific signature for each detected object to build tracklets. On the other hand, we associate these mini-trajectories in order to have complete trajectory.

    References

    [1]
    http://www.cvg.reading.ac.uk/PETS2009/a.html.
    [2]
    J. Badie and F. Bremond. Global tracker: an online evaluation framework to improve tracking quality. In Advanced Video and Signal Based Surveillance (AVSS), 2014 11th IEEE International Conference on, pages 25--30. IEEE, 2014.
    [3]
    S.-H. Bae and K.-J. Yoon. Robust online multi-object tracking based on tracklet confidence and online discriminative appearance learning. In 2014 IEEE Conference on Computer Vision and Pattern Recognition, pages 1218--1225. IEEE, 2014.
    [4]
    A. Dehghan, Y. Tian, P. H. Torr, and M. Shah. Target identity-aware network flow for online multiple target tracking. In 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1146--1154. IEEE, 2015.
    [5]
    R. Girshick. Fast r-cnn. In Proceedings of the IEEE International Conference on Computer Vision, pages 1440--1448, 2015.
    [6]
    Y. Mao and Z. Yin. Training a scene-specific pedestrian detector using tracklets. In 2015 IEEE Winter Conference on Applications of Computer Vision, pages 170--176. IEEE, 2015.
    [7]
    Y. Pang, Y. Yuan, X. Li, and J. Pan. Efficient hog human detection. Signal Processing, 91(4):773--781, 2011.
    [8]
    S. Ren, K. He, R. Girshick, and J. Sun. Faster r-cnn: Towards real-time object detection with region proposal networks. In Advances in neural information processing systems, pages 91--99, 2015.
    [9]
    P. Viola and M. Jones. Rapid object detection using a boosted cascade of simple features. In Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on, volume 1, pages I--511. IEEE, 2001.
    [10]
    Q. Yu and G. Medioni. Map-enhanced detection and tracking from a moving platform with local and global data association. In Motion and Video Computing, 2007. WMVC'07. IEEE Workshop on, pages 3--3. IEEE, 2007.

    Cited By

    View all
    • (2019)An Embedded Computer-Vision System for Multi-Object Detection in Traffic SurveillanceIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2018.287661420:11(4006-4018)Online publication date: Nov-2019
    1. Tracking multi-object using tracklet and Faster R-CNN: PhD Forum

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Other conferences
      ICDSC '16: Proceedings of the 10th International Conference on Distributed Smart Camera
      September 2016
      242 pages
      ISBN:9781450347860
      DOI:10.1145/2967413
      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]

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 12 September 2016

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. Faster R-CNN
      2. Tracking multi-object
      3. Tracklet

      Qualifiers

      • Short-paper
      • Research
      • Refereed limited

      Conference

      ICDSC '16

      Acceptance Rates

      Overall Acceptance Rate 92 of 117 submissions, 79%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)3
      • Downloads (Last 6 weeks)0
      Reflects downloads up to 27 Jul 2024

      Other Metrics

      Citations

      Cited By

      View all
      • (2019)An Embedded Computer-Vision System for Multi-Object Detection in Traffic SurveillanceIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2018.287661420:11(4006-4018)Online publication date: Nov-2019

      View Options

      Get Access

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media