This paper presents the outcomes of the PETS2021 challenge held in conjunction with AVSS2021 and sponsored by the EU FOLDOUT project. The challenge comprises the publication of a novel video surveillance dataset on through-foliage detection, the defined challenges addressing person detection and tracking in fragmented occlusion scenarios, and quantitative and qualitative performance evaluation of challenge results submitted by six worldwide participants. The results show that while several detection and tracking methods achieve overall good results, through-foliage detection and tracking remains a challenging task for surveillance systems especially as it serves as the input to behaviour (threat) recognition.
|Title of host publication||AVSS 2021 - 17th IEEE International Conference on Advanced Video and Signal-Based Surveillance|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Publication status||Published - 2021|
|Event||17th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2021 - Virtual, Online, United States|
Duration: 2021 Nov 16 → 2021 Nov 19
|Name||AVSS 2021 - 17th IEEE International Conference on Advanced Video and Signal-Based Surveillance|
|Conference||17th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2021|
|Period||21/11/16 → 21/11/19|
Bibliographical noteFunding Information:
This challenge is sponsored by the EU funded project FOLDOUT: Through Foliage Detection of Illegal Cross-Border Activities (https://foldout.eu).
This research was funded by EU H2020 Research and Innovation Programme under grant agreement no. 787021 (FOLDOUT). We thank Zhongqun Zhang, Univ. of Birmingham, UK for the valuable discussion and help during the evaluation.
© 2021 IEEE.
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Signal Processing
- Media Technology