@inproceedings{3027030a2c1449549d3b181b11338f24,
title = "P-Benchmark: A Benchmark for Video Surveillance Using UAVs",
abstract = "Video surveillance is one of the most essential tasks in the real world. Therefore, many state-of-the-art tracking algorithms were developed that can be applied for general video surveillance purposes. However, due to lack of dedicated benchmark for pedestrian tracking algorithms, this domain is least explored. Further, the commercial availability and low cost make unmanned aerial vehicles (UAVs) more suitable for tracking from the sky. Therefore, the present work proposes a new benchmark using aerial datasets for visual pedestrian tracking by UAVs. This newly developed p-benchmark consists of 117 real-world image sequences to exhaustively evaluate the performance of different Siamese network-based trackers, which may act as a baseline.",
author = "Himanshu Gupta and Deepak Jangid and Sourabh Verma and Verma, \{Om Prakash\} and Sharma, \{Tarun K.\}",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.; 2nd International Conference on Machine Intelligence for Research and Innovations, MAiTRI 2024 Summit ; Conference date: 21-06-2024 Through 23-06-2024",
year = "2026",
doi = "10.1007/978-981-96-7614-9\_29",
language = "English",
isbn = "9789819676132",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "393--403",
editor = "Verma, \{Om Prakash\} and Lipo Wang and Rajesh Kumar and Anupam Yadav and Rout, \{Ranjeet Kumar\}",
booktitle = "Machine Intelligence for Research and Innovations - Proceedings of MAiTRI 2024",
address = "Germany",
}