{"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/motion-feature-augmented-recurrent-neural","title":"Motion Feature Augmented Recurrent Neural Network for Skeleton-based Dynamic Hand Gesture Recognition","arxiv_id":"1708.03278","date":"2017-08-10","proceeding":null,"authors":["Xinghao Chen","Hengkai Guo","Guijin Wang","Li Zhang"],"abstract":"Dynamic hand gesture recognition has attracted increasing interests because\nof its importance for human computer interaction. In this paper, we propose a\nnew motion feature augmented recurrent neural network for skeleton-based\ndynamic hand gesture recognition. Finger motion features are extracted to\ndescribe finger movements and global motion features are utilized to represent\nthe global movement of hand skeleton. These motion features are then fed into a\nbidirectional recurrent neural network (RNN) along with the skeleton sequence,\nwhich can augment the motion features for RNN and improve the classification\nperformance. Experiments demonstrate that our proposed method is effective and\noutperforms start-of-the-art methods.","url_abs":"http://arxiv.org/abs/1708.03278v1","url_pdf":"http://arxiv.org/pdf/1708.03278v1.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":[],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"gesture-recognition","task_name":"Gesture Recognition"},{"task_slug":"hand-gesture-recognition","task_name":"Hand Gesture Recognition"},{"task_slug":"hand-gesture-recognition-1","task_name":"Hand-Gesture Recognition"},{"task_slug":"skeleton-based-action-recognition","task_name":"Skeleton Based Action Recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/hand-gesture-recognition-on-dhg-14","task":"Hand Gesture Recognition","dataset":"DHG-14","model":"MFANet","rank_in_archive_order":12,"of":13,"metrics":{"Accuracy":"84.68"},"uses_additional_data":false},{"leaderboard":"/sota/hand-gesture-recognition-on-dhg-28","task":"Hand Gesture Recognition","dataset":"DHG-28","model":"MFANet","rank_in_archive_order":9,"of":9,"metrics":{"Accuracy":"80.32"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}