74 / 2023-09-01 18:43:05
Research on Real-Time Pedestrian Detection Based on Infrared-Visible Image Fusion
Multispectral Image,Image Fusion,Pedestrian Detection,Deep Learning
Final Paper
Ziqin Shang / China Mobile (Hangzhou) Information Technology Co., Ltd.
Baoping Cheng / China Mobile (Hangzhou) Information Technology Co., Ltd.
Xiaoyan Xie / China Mobile (Hangzhou) Information Technology Co., Ltd.
Tao Fu / China Mobile (Hangzhou) Information Technology Co., Ltd.
Zijian Wu / China Mobile (Hangzhou) Information Technology Co., Ltd.
With the advancement of AI technology and hardware, intelligent surveillance systems are becoming increasingly widespread, bringing more and more complex application scene. Pedestrian detection, as one of the tasks within such systems, faces more challenges consequently. Current pedestrian detection methods primarily rely on visible-light modality, limiting their performance and robustness. Introducing an additional modality, such as infrared, to improve performance imposes higher demands on platforms and resources. Therefore, multi-spectral image fusion emerges as a promising technique to enhance pedestrian detection. This paper proposes a pedestrian detection framework based on infrared-visible light image fusion. Additionally, three fusion methods are employed and compared against single-spectral results using existing detection model, which validate the potential for improving pedestrian detection performance.
Important Date
  • Conference Date

    Nov 02

    2023

    to

    Nov 04

    2023

  • Dec 15 2023

    Draft paper submission deadline

  • Dec 20 2023

    Registration deadline

Sponsored By
IEEE Instrumentation and Measurement Society
Xidian University