{"doi":"10.1109/tencon.2006.343858","title":"3D Head Pose Estimation Using Non-rigid Structure-from-motion and Point Correspondence","abstract":null,"journal":"TENCON 2006 - 2006 IEEE Region 10 Conference","year":2006,"id":46865,"datarank":0.6461554835353942,"base_score":2.3978952727983707,"endowment":2.3978952727983707,"self_citation_contribution":0.3596842909197557,"citation_network_contribution":0.28647119261563847,"self_endowment_contribution":0.3596842909197557,"citer_contribution":0.28647119261563847,"corpus_percentile":null,"corpus_rank":null,"citation_count":10,"citer_count":10,"citers_with_citation_signal":9,"citers_with_endowment":9,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":18588,"name":"Chao Zhang","orcid":"0000-0001-8126-8145","position":1,"is_corresponding":false},{"id":216695,"name":"Zhenghui Gui","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"3D Head Pose Estimation Using Non-rigid Structure-from-motion and Point Correspondence","abstract":"This paper addresses tracking and 3D pose estimation of human faces with large pose and expression changes in video sequences obtained from an un-calibrated monocular camera. The classical pose estimation methods suffer from two disadvantages: (1) a 3D head model or a reference frame is always needed and the camera should be calibrated in advance; (2) it is difficult to deal with non-rigid motion, which is very common for human faces. In this paper, we present a pose estimation system, which is able to overcome the above disadvantages. For each frame, a 2D active appearance model is adopted to reliably track the face and facial features with large pose and expression variations. Then we utilize a recently developed non-rigid structure from motion (SFM) technique to recover the 3D face shape. Instead of direct using the rotation matrix resulted from SFM, we propose a method to use robust statistics and 3D-2D feature point correspondence to accurately recover the 3D head pose. Our experiments have demonstrated the effectiveness and efficiency of the approach.","is_dataset_classified":null,"base_score":2.3978952727983707,"endowment":2.3978952727983707,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19910364","pmcid":null,"openalex_id":"https://openalex.org/W2129348295","authors":[],"funders":[],"total_grants":0,"fwci":0.3106,"citation_percentile":0.61950892,"influential_citations":0,"citation_trend":[{"year":2012,"count":2},{"year":2014,"count":2},{"year":2021,"count":1}],"oa_status":"closed","license":null,"oa_locations":[{"url":"http://xplorestaging.ieee.org/ielx5/4142120/4142121/04142521.pdf?arnumber=4142521","host_type":"publisher"},{"url":"https://doi.org/10.1109/tencon.2006.343858","host_type":""}],"fields_of_study":["Face recognition and analysis","Video Surveillance and Tracking Methods","Advanced Vision and Imaging","Computer Science"],"mesh_terms":[],"keywords":["Computer vision","Artificial intelligence","Pose","Articulated body pose estimation","Computer science","3D pose estimation","Face (sociological concept)","Motion estimation","Feature (linguistics)","Structure from motion","Monocular","Rotation (mathematics)","Facial expression","Frame (networking)","Point (geometry)","Motion (physics)","Tracking (education)","Head (geology)","Mathematics"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-14T20:48:46.589913Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}