Research Article
A Panoramic Video Face Detection System Design and Implement
@INPROCEEDINGS{10.1007/978-3-030-41117-6_8, author={Hang Zhao and Dian Liu and Bin Tan and Songyuan Zhao and Jun Wu and Rui Wang}, title={A Panoramic Video Face Detection System Design and Implement}, proceedings={Communications and Networking. 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 -- December 1, 2019, Proceedings, Part II}, proceedings_a={CHINACOM PART 2}, year={2020}, month={2}, keywords={Panorama Face detection SURF CUDA}, doi={10.1007/978-3-030-41117-6_8} }- Hang Zhao
Dian Liu
Bin Tan
Songyuan Zhao
Jun Wu
Rui Wang
Year: 2020
A Panoramic Video Face Detection System Design and Implement
CHINACOM PART 2
Springer
DOI: 10.1007/978-3-030-41117-6_8
Abstract
A panorama is a wide-angle view picture with high-resolution, usually composed of multiple images, and has a wide range of applications in surveillance and entertainment. This paper presents a end-to-end real-time panoramic face detection video system, which generates panorama video efficiently and effectively with the ability of face detection. We fix the relative position of the camera and use the speeded up robust features (SURF) matching algorithm to calibrate the cameras in the offline stage. In the online stage, we improve the parallel execution speed of image stitching using the latest compute unified device architecture (CUDA) technology. The proposed design fulfils high-quality automatic image stitching algorithm to provide a seamless panoramic image with 6k resolution at 25 fps. We also design a convolutional neural network to build a face detection model suitable for panorama input. The model performs very well especially in small faces and multi-faces, and can maintain the detection speed of 25 fps at high resolution.
