J. M. Rehg, K. P. Murphy, and P. W. Fieguth. Vision-based speaker detection using bayesian networks. In Proceedings of Conference on Computer Vision and Pattern Recognition, volume 2, pages 110--116, Ft. Collins, CO, June 1999. Home/Search Document Details and Download
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General Examination on Technical Area: Recognizing human activity .. - Sawhney (Correct)
....in MUDs, text based multi player adventure games, based on training data of action location probabilities over time. Finally DBNs have been recently applied towards visual sensor fusion, combining the output of several vision algorithms in an interactive kiosk to detect the presence of a speaker [Rehg99]. They have also been applied towards visual surveillance and analysis tasks, requiring the recognition of complex multi agent actions in a scene [Intille98] Figure 4: A Dynamic Bayesian network (DBN) showing control layer states X 1 . X 3 factored into composite variable nodes S 1 ,S 2 ....
Rehg, J. M., Murphy, K. P., Fieguth, P. W. 1999. Vision-Based Speaker Detection Using Bayesian Networks. In Proceedings of Computer Vision and Pattern Recognition, pp. 110-116.
Look Who's Talking: Speaker Detection Using Video And Audio.. - Cutler, Davis (2000) (10 citations) (Correct)
.... work done in locating speakers using arrays of microphones (e.g. 16] and in identifying a specific individual speaking (e.g. 12] Audio data can be used to animate lips for animated and real characters [1] 2] Vision based techniques have also been used to detect people in front of kiosks [11] [4] There are text to speech systems which utilize hand coded phoneme to viseme rules to animate characters [17] We are not aware of any previous work done that exploits the audio visual correlation in speaking to detect speakers (spatially and temporally) in video with a single microphone. ....
J. M. Rehg, K. P. Murphy, and P. W. Fieguth. Vision-based speaker detection using bayesian networks. In Proceedings of the Computer Vision and Pattern Recognition, 1999.
Boosting and Structure Learning in Dynamic Bayesian .. - Choudbury, Rehg.. (2002) (1 citation) Self-citation (Rehg) (Correct)
No context found.
J. M. Rehg, K. P. Murphy, and P. W. Fieguth. Vision-based speaker detection using bayesian networks. In Proceedings of Conference on Computer Vision and Pattern Recognition, volume 2, pages 110--116, Ft. Collins, CO, June 1999.
Vision-Based Speaker Detection Using Bayesian Networks - Rehg, Murphy (1999) (3 citations) Self-citation (Rehg Murphy Fieguth) (Correct)
....close the loop between sensing and action in a sound, decision theoretic manner [6] Acknowledgements We would like to thank Henry Rowley for his help with the CMU face detector. We would also like to thank the reviewers for their detailed comments. An earlier version of this paper appeared as [18]. ....
J. M. Rehg, K. P. Murphy, and P. W. Fieguth. Visionbased speaker detection using bayesian networks. In Workshop on Perceptual User-Interfaces, pages 107-- 112, 1998.
Vision-Based Speaker Detection Using Bayesian Networks - Rehg, Murphy, al. (1999) (3 citations) Self-citation (Rehg Murphy Fieguth) (Correct)
....close the loop between sensing and action in a sound, decision theoretic manner [6] Acknowledgements We would like to thank Henry Rowley for his help with the CMU face detector. We would also like to thank the reviewers for their detailed comments. An earlier version of this paper appeared as [18]. ....
J. M. Rehg, K. P. Murphy, and P. W. Fieguth. Visionbased speaker detection using bayesian networks. In Workshop on Perceptual User-Interfaces, pages 107-- 112, 1998.
Multimodal Speaker Detection using Input/Output Dynamic.. - Pavlovic, Garg, Rehg Self-citation (Rehg) (Correct)
....improvements in detection accuracy. We present these results in the context of a network architecture of Figure 1 which infers the state of the speaker who actively interacts with the Genie Casino game. Our evaluation of the learned DBN model indicates its superiority over previous static [7] and dynamic [3, 5] detection models. 2 Speaker Detection An estimate of the persons state (whether s he is or isn t a speaker) is important for the reliable functioning of any speech based interface. We argue that for a person to be an active speaker, s he must be expected to speak, face the ....
....speech input from the user. We use a set of five off the shelf visual and audio sensors: the CMU face detector [8] a Gaussian skin color detector [10] a face texture detector, a mouth motion detector, and an audio silence detector. A detailed description of these detectors can be found in [7]. Contextual input provides the state of the application (the blackjack game) which may help in inferring the state of the user. 2.1 Bayesian networks for speaker detection with continuous sensors and contextual input We adopt a modular approach towards the design of the Bayesian network for ....
J. M. Rehg, K. P. Murphy, and P. W. Fieguth, "Vision-based speaker detection using bayesian networks," in Proc. IEEE Conf. on Computer Vision and Pattern Recognition, (Ft. Collins, CO), pp. 110--116, 1999.
Audio-Visual Speaker Detection using Dynamic Bayesian.. - Garg, Pavlovic, Rehg, Huang (2000) (5 citations) Self-citation (Rehg) (Correct)
No context found.
J. M. Rehg, K. P. Murphy, and P. W. Feiguth, "Visionbased speaker detection using bayesian networks," in Proc. IEEE Conf. on Computer Vision and Pattern Recognition, (Ft. Collins, CO), 1999.
Classifiying Offensive Sites Based on Image Content - Arentz, Olstad (Correct)
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J. M. Rehg, K. P. Murphy, and P. W. Fieguth. Vision-based speaker detection using bayesian networks. pages 110--116.
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