Citation Abstract We demonstrate the automatic transfer of an assembly task from human to robot. This work extends efforts showing the utility of linguistic models in verifiable robot control policies by now performing real visual analysis of human demonstrations to automatically extract a policy for the task. This method tokenizes each human demonstration into a […]
Citation P. Yin, T. Starner, H. Hamilton, I. Essa, and J. M. Rehg (2009), “Learning Basic Units in American Sign Language using Discriminative Segmental Feature Selection,” in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2009, pp. 4757-4760. [BIBTEX] @InProceedings{ 2009-Yin-LBUASLUDSFS, author = {P. Yin and T. Starner and H. Hamilton and I. […]
Pei Yin, Irfan Essa, James Rehg, Thad Starner (2008) “Discriminative Feature Selection for Hidden Markov Models using Segmental Boosting”, ICASSP 2008 – March 30 – April 4, 2008 – Las Vegas, Nevada, U.S.A. (Paper: MLSP-P3.D8, Session: Pattern Recognition and Classification II, Time: Thursday, April 3, 15:30 – 17:30, Topic: Machine Learning for Signal Processing: Learning […]
Mitch Parry (2007), Separation and Analysis of Multichannel Signals PhD Thesis [PDF], Georgia Institute of Techniology, College of Computing, Atlanta, GA. (Advisor: Irfan Essa) Abstract This thesis examines a large and growing class of digital signals that capture the combined effect of multiple underlying factors. In order to better understand these signals, we would like […]
Yin, Pei Criminisi, Antonio Winn, John Essa, Irfan (2007), Tree-based Classifiers for Bilayer Video Segmentation In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2007. CVPR ’07, 17-22 June 2007, page(s): 1 – 8, Location: Minneapolis, MN, USA, ISBN: 1-4244-1180-7, Digital Object Identifier: 10.1109/CVPR.2007.383008 Abstract This paper presents an algorithm for the automatic segmentation of monocular videos […]
Parry, R.M. Essa, I. (2007) “Incorporating Phase Information for Source Separation via Spectrogram Factorization.” In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. 15-20 April 2007, Volume: 2, page(s): II-661 – II-66, Honolulu, HI, ISSN: 1520-6149, ISBN: 1-4244-0728-1, INSPEC Accession Number:9497202, Digital Object Identifier: 10.1109/ICASSP.2007.366322 Abstract Spectrogram factorization methods have been proposed for single channel source separation and audio […]
Parry, R.M. Essa, I. (2006) “Source Detection Using Repetitive Structure (IEEEXplore).” Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, 2006. ICASSP 2006, Publication Date: 14-19 May 2006, Volume: 4, page(s): IV – IV, Location: Toulouse, ISSN: 1520-6149, ISBN: 1-4244-0469-X, INSPEC Accession Number:9154520, Digital Object Identifier: 10.1109/ICASSP.2006.1661163 Abstract Blind source separation algorithms typically require that the number of sources are known in advance. […]
Pei Yin Essa, I. Rehg, J.M. (2004) “Asymmetrically boosted HMM for speech reading,”, In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004 (CVPR 2004). Publication Date: 27 June-2 July 2004, Volume: 2, On page(s): II-755 – II-761 Vol.2 ISSN: 1063-6919, ISBN: 0-7695-2158-, INSPEC Accession Number:8161546, Digital Object Identifier: 10.1109/CVPR.2004.1315240 […]
Yin, P. Essa, I. Rehg, J.M. (2003) “Boosted audio-visual HMM for speech reading.” In Proceedings Thirty-Seventh Asilomar Conference on Signals, Systems and Computers, 2003. Date: 9-12 Nov. 2003, Volume: 2, On page(s): 2013 – 2018 Vol.2, , ISBN: 0-7803-8104-1, INSPEC Accession Number:8555396, Digital Object Identifier: 10.1109/ACSSC.2003.1292334 Abstract We propose a new approach for combining acoustic […]
Award#0205507 – ITR: Analysis of Complex Audio-Visual Events Using Spatially Distributed Sensors ABSTRACT We propose to develop a comprehensive framework for the joint analysis of audio-visual signals obtained from spatially distributed microphones and cameras. We desire solutions to the audio-visual sensing problem that will scale to an arbitrary number of cameras and microphones and can […]