A CPU-GPU Hybrid People Counting System for Real-World Airport Scenarios Using Arbitrary Oblique View Cameras
Abstract
This work <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> presents a real-time hybrid CPU-GPU implementation of a practical people counting system, developed for real-world airport scenarios and using the existing airport single cameras. The cameras are characterized by low quality images and are installed in arbitrary oblique viewing angles and heights relative to the ground plane. The scenes are characterized by large field of view, large scale variations of people size, high clutter, and in particular severe occlusions. In addition, people tend to remain long at rest while queuing. Furthermore, real-time performance is required and no elaborate camera calibration is feasible. Our system is based on the fusion of two approaches. The first one is holistic, namely a texture based classification. The second approach utilizes the fast directional Chamfer matching algorithm with variable size ellipse templates to detect heads. Using a probabilistic multi-class SVM classifier for both approaches, the output of the 2 classifier is further fused, yielding a unified prediction.
Cite
Text
Schreiber and Rauter. "A CPU-GPU Hybrid People Counting System for Real-World Airport Scenarios Using Arbitrary Oblique View Cameras." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2012. doi:10.1109/CVPRW.2012.6238899Markdown
[Schreiber and Rauter. "A CPU-GPU Hybrid People Counting System for Real-World Airport Scenarios Using Arbitrary Oblique View Cameras." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2012.](https://mlanthology.org/cvprw/2012/schreiber2012cvprw-cpugpu/) doi:10.1109/CVPRW.2012.6238899BibTeX
@inproceedings{schreiber2012cvprw-cpugpu,
title = {{A CPU-GPU Hybrid People Counting System for Real-World Airport Scenarios Using Arbitrary Oblique View Cameras}},
author = {Schreiber, David and Rauter, Michael},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2012},
pages = {83-88},
doi = {10.1109/CVPRW.2012.6238899},
url = {https://mlanthology.org/cvprw/2012/schreiber2012cvprw-cpugpu/}
}