NDLI: Automatic fiducial points detection for facial expressions using scale invariant feature

Content Provider	IEEE Xplore Digital Library
Author	Tie Yun Ling Guan
Copyright Year	2009
Description	Author affiliation: Ryerson Multimedia Research Lab, Ryerson University, Toronto, Canada (Tie Yun; Ling Guan)
Abstract	Detecting fiducial points successfully in facial images or video sequences can play an important role in numerous facial image interpretation tasks such as face detection and identification, facial expression recognition, emotion recognition, and face image database management. In this paper we propose an automatic and robust method of facial fiducial point's detection for facial expressions analysis in video sequences using scale invariant feature based Adaboost classifiers. Face region is first located using the face detector with local normalization and optimal adaptive correlation technique. Candidate points are then selected over the face region using local scale-space extrema detection. The scale invariant feature for each candidate point is extracted for further examination. We choose 26 fiducial points on the face region from training samples to build the fiducial point detectors with Adaboost classifiers. All the candidate points in the test samples are examined through these detectors. Finally, all the 26 facial fiducial points are located on each frame of the test samples. Cohn-Kanade database and Mind Reading DVD are used for experiment. The results show that our method achieves a good performance of 90.69% average recognition rate.
Starting Page	1
Ending Page	6
File Size	754626
Page Count	6
File Format	PDF
ISBN	9781424444632
DOI	10.1109/MMSP.2009.5293308
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-10-05
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Face detection Detectors Video sequences Emotion recognition Testing Face recognition Image recognition Image databases Robustness Image sequence analysis
Content Type	Text
Resource Type	Article

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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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