Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Tools for Protecting the Privacy of Specific Individuals in Video | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 75427 9 pages doi 2007 75427 Research Article Tools for Protecting the Privacy of Specific Individuals in Video Datong Chen Yi Chang Rong Yan and Jie Yang School of Computer Science Carnegie Mellon University Pittsburgh PA 15213 USA Received 25 July 2006 Revised 28 September 2006 Accepted 31 October 2006 Recommended by Ying Wu This paper presents a system for protecting the privacy of specific individuals in video recordings. We address the following two problems automatic people identification with limited labeled data and human body obscuring with preserved structure and motion information. In order to address the first problem we propose a new discriminative learning algorithm to improve people identification accuracy using limited training data labeled from the original video and imperfect pairwise constraints labeled from face obscured video data. We employ a robust face detection and tracking algorithm to obscure human faces in the video. Our experiments in a nursing home environment show that the system can obtain a high accuracy of people identification using limited labeled data and noisy pairwise constraints. The study result indicates that human subjects can perform reasonably well in labeling pairwise constraints with the face masked data. For the second problem we propose a novel method of body obscuring which removes the appearance information of the people while preserving rich structure and motion information. The proposed approach provides a way to minimize the risk of exposing the identities of the protected people while maximizing the use of the captured data for activity behavior analysis. Copyright 2007 Datong Chen et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. .
