{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/uav-gesture-a-dataset-for-uav-control-and","title":"UAV-GESTURE: A Dataset for UAV Control and Gesture Recognition","arxiv_id":"1901.02602","date":"2019-01-09","proceeding":null,"authors":["Asanka G Perera","Yee Wei Law","Javaan Chahl"],"abstract":"Current UAV-recorded datasets are mostly limited to action recognition and\nobject tracking, whereas the gesture signals datasets were mostly recorded in\nindoor spaces. Currently, there is no outdoor recorded public video dataset for\nUAV commanding signals. Gesture signals can be effectively used with UAVs by\nleveraging the UAVs visual sensors and operational simplicity. To fill this gap\nand enable research in wider application areas, we present a UAV gesture\nsignals dataset recorded in an outdoor setting. We selected 13 gestures\nsuitable for basic UAV navigation and command from general aircraft handling\nand helicopter handling signals. We provide 119 high-definition video clips\nconsisting of 37151 frames. The overall baseline gesture recognition\nperformance computed using Pose-based Convolutional Neural Network (P-CNN) is\n91.9 %. All the frames are annotated with body joints and gesture classes in\norder to extend the dataset's applicability to a wider research area including\ngesture recognition, action recognition, human pose recognition and situation\nawareness.","url_abs":"http://arxiv.org/abs/1901.02602v1","url_pdf":"http://arxiv.org/pdf/1901.02602v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"uav-gesture-a-dataset-for-uav-control-and","repo_url":"https://github.com/asankagp/UAV-GESTURE","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"action-recognition-in-videos","task_name":"Action Recognition"},{"task_slug":"gesture-recognition","task_name":"Gesture Recognition"},{"task_slug":"object-tracking","task_name":"Object Tracking"},{"task_slug":"action-recognition","task_name":"Temporal Action Localization"}],"methods":[],"datasets_introduced":[{"slug":"uav-gesture","name":"UAV-GESTURE","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1901.02602","atlas_url":"https://app.syntology.ai/?focus=1901.02602","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}