ML Anthology

Real-Time, Embedded Scene Invariant Crowd Counting Using Scale-Normalized Histogram of Moving Gradients (HoMG)

Parthipan Siva, Mohammad Javad Shafiee, Michael Jamieson, Alexander Wong
CVPRW 2016 pp. 885-892
doi:10.1109/CVPRW.2016.115 /cvprw/2016/siva2016cvprw-realtime/

Abstract

Automated crowd counting has garnered significant interest for video surveillance. This paper proposes a novel scene invariant crowd counting algorithm designed for high accuracy yet low computational complexity in order to facilitate widespread use in real-time embedded video analytics systems. A novel low-complexity, scale-normalized feature called Histogram of Moving Gradients (HoMG) is introduced for highly effective spatiotemporal representation of crowds within a video. Real-time crowd region detection is achieved via boosted cascade of weak classifiers based on HoMG features. Based on the detected crowd regions, linear support vector regression (SVR) of crowd-region HoMG features is introduced for real-time crowd counting. Experimental results using a multi-scene crowd dataset show that the proposed algorithm outperforms state-of-the-art crowd counting algorithms while embedded on modern surveillance cameras. Thus demonstrating the efficacy of the proposed method for accurate, real-time, embedded crowd analysis.

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Cite

Text

Siva et al. "Real-Time, Embedded Scene Invariant Crowd Counting Using Scale-Normalized Histogram of Moving Gradients (HoMG)." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2016. doi:10.1109/CVPRW.2016.115

Markdown

[Siva et al. "Real-Time, Embedded Scene Invariant Crowd Counting Using Scale-Normalized Histogram of Moving Gradients (HoMG)." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2016.](https://mlanthology.org/cvprw/2016/siva2016cvprw-realtime/) doi:10.1109/CVPRW.2016.115

BibTeX

@inproceedings{siva2016cvprw-realtime,
  title     = {{Real-Time, Embedded Scene Invariant Crowd Counting Using Scale-Normalized Histogram of Moving Gradients (HoMG)}},
  author    = {Siva, Parthipan and Shafiee, Mohammad Javad and Jamieson, Michael and Wong, Alexander},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2016},
  pages     = {885-892},
  doi       = {10.1109/CVPRW.2016.115},
  url       = {https://mlanthology.org/cvprw/2016/siva2016cvprw-realtime/}
}