Comparison of Image Transform-Based Features for Visual Speech Recognition in Clean and Corrupted Videos. (13th January 2008)

• Record Type: Journal Article
• Authors: Seymour, Rowan; Stewart, Darryl; Ming, Ji
• Other Names: Nikolaidis Nikos Academic Editor.
• Is Part Of: EURASIP journal on image and video processing. Volume 2008(2008)
• Publication Date: 2008-01-13
• Subjects: Image processing -- Digital techniques -- Periodicals; Digital video -- Periodicals; Traitement d'images; Vidéo numérique; Digital video; Image processing -- Digital techniques; Periodicals; Electronic journal; Electronic journals; 621.367
• DOI: 10.1155/2008/810362
• Languages: English
• ISSNs: 1687-5176

Abstract

Abstract : We present results of a study into the performance of a variety of different image transform-based feature types for speaker-independent visual speech recognition of isolated digits. This includes the first reported use of features extracted using a discrete curvelet transform. The study will show a comparison of some methods for selecting features of each feature type and show the relative benefits of both static and dynamic visual features. The performance of the features will be tested on both clean video data and also video data corrupted in a variety of ways to assess each feature type's robustness to potential real-world conditions. One of the test conditions involves a novel form of video corruption we call jitter which simulates camera and/or head movement during recording.