NDLI: Robust semi-automatic head pose labeling for real-world face video sequences

Content Provider	Springer Nature Link
Author	Demirkus, Meltem Clark, James J. Arbel, Tal
Copyright Year	2013
Abstract	Automatic head pose estimation from real-world video sequences is of great interest to the computer vision community since pose provides prior knowledge for tasks, such as face detection and classification. However, developing pose estimation algorithms requires large, labeled real-world video databases on which computer vision systems can be trained and tested. Manual labeling of each frame is tedious, time consuming, and often difficult due to the high uncertainty in head pose angle estimate, particularly in unconstrained environments that include arbitrary facial expression, occlusion, illumination etc. To overcome these difficulties, a semi-automatic framework is proposed for labeling temporal head pose in real-world video sequences. The proposed multi-stage labeling framework first detects a subset of frames with distinct head poses over a video sequence, which is then manually labeled by the expert to obtain the ground truth for those frames. The proposed framework provides a continuous head pose label and corresponding confidence value over the pose angles. Next, the interpolation scheme over a video sequence estimates i) labels for the frames without manual labels and ii) corresponding confidence values for interpolated labels. This confidence value permits an automatic head pose estimation framework to determine the subset of frames to be used for further processing, depending on the labeling accuracy required. The experiments performed on an in-house, labeled, large, real-world face video database (which will be made publicly available) show that the proposed framework achieves 96.98 % labeling accuracy when manual labeling is only performed on 30 % of the video frames.
Starting Page	495
Ending Page	523
Page Count	29
File Format	PDF
ISSN	13807501
Journal	Multimedia Tools and Applications
Volume Number	70
Issue Number	1
e-ISSN	15737721
Language	English
Publisher	Springer US
Publisher Date	2013-01-25
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Semi-automatic labeling Real-world video sequence Head pose Automatic face tracking Bag-of-words Manifold Multimedia Information Systems Computer Communication Networks Data Structures, Cryptology and Information Theory Special Purpose and Application-Based Systems
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Hardware and Architecture Software Media Technology

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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