{"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/rule-of-thumb-deep-derotation-for-improved","title":"Rule Of Thumb: Deep derotation for improved fingertip detection","arxiv_id":"1507.05726","date":"2015-07-21","proceeding":null,"authors":["Aaron Wetzler","Ron Slossberg","Ron Kimmel"],"abstract":"We investigate a novel global orientation regression approach for articulated\nobjects using a deep convolutional neural network. This is integrated with an\nin-plane image derotation scheme, DeROT, to tackle the problem of per-frame\nfingertip detection in depth images. The method reduces the complexity of\nlearning in the space of articulated poses which is demonstrated by using two\ndistinct state-of-the-art learning based hand pose estimation methods applied\nto fingertip detection. Significant classification improvements are shown over\nthe baseline implementation. Our framework involves no tracking, kinematic\nconstraints or explicit prior model of the articulated object in hand. To\nsupport our approach we also describe a new pipeline for high accuracy magnetic\nannotation and labeling of objects imaged by a depth camera.","url_abs":"http://arxiv.org/abs/1507.05726v1","url_pdf":"http://arxiv.org/pdf/1507.05726v1.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":"fingertip-detection","task_name":"Fingertip Detection"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"hand-pose-estimation","task_name":"Hand Pose Estimation"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[{"slug":"handnet","name":"HandNet","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}