{"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/web-based-visualisation-of-head-pose-and","title":"Web-based visualisation of head pose and facial expressions changes: monitoring human activity using depth data","arxiv_id":"1703.03949","date":"2017-03-11","proceeding":null,"authors":["Grigorios Kalliatakis","Nikolaos Vidakis","Georgios Triantafyllidis"],"abstract":"Despite significant recent advances in the field of head pose estimation and\nfacial expression recognition, raising the cognitive level when analysing human\nactivity presents serious challenges to current concepts. Motivated by the need\nof generating comprehensible visual representations from different sets of\ndata, we introduce a system capable of monitoring human activity through head\npose and facial expression changes, utilising an affordable 3D sensing\ntechnology (Microsoft Kinect sensor). An approach build on discriminative\nrandom regression forests was selected in order to rapidly and accurately\nestimate head pose changes in unconstrained environment. In order to complete\nthe secondary process of recognising four universal dominant facial expressions\n(happiness, anger, sadness and surprise), emotion recognition via facial\nexpressions (ERFE) was adopted. After that, a lightweight data exchange format\n(JavaScript Object Notation-JSON) is employed, in order to manipulate the data\nextracted from the two aforementioned settings. Such mechanism can yield a\nplatform for objective and effortless assessment of human activity within the\ncontext of serious gaming and human-computer interaction.","url_abs":"http://arxiv.org/abs/1703.03949v2","url_pdf":"http://arxiv.org/pdf/1703.03949v2.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":"web-based-visualisation-of-head-pose-and","repo_url":"https://github.com/eric-erki/Visualising-Facial-Expression-Changes","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"emotion-recognition","task_name":"Emotion Recognition"},{"task_slug":"facial-expression-recognition-1","task_name":"Facial Expression Recognition"},{"task_slug":"facial-expression-recognition","task_name":"Facial Expression Recognition (FER)"},{"task_slug":"head-pose-estimation","task_name":"Head Pose Estimation"},{"task_slug":"pose-estimation","task_name":"Pose Estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}