R. Cipolla, A. Pentland, Computer Vision for Human--Machine Interaction, Cambridge University Press, Cambridge, 1998.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....special cares are taken to deal with the large number of gestures, which are partially similar. Keywords: HMM, PCA, Graph Matching, Kalman Filter, Tracking. 1. Introduction The use of hand gesture as a more natural way in Human Computer Interaction has been addressed in the literature [1]. Statistical methods are from the very popular approaches to the recognition of hand gestures. However, many approaches have been introduced. Spariotemporal hand gesture recognition using neural networks [2] 3] temporal models for gesture recognition [4] spatial modelling of gestures [5] 6] ....

R. Cipolla and A. Pentland, Computer Vision for Human-Machine Interaction, Cambridge University Press, 1998.

....guiding a pilot driving an aircraft to the parking, showing the size of something (e.g. a fish) etc. Tracking the hands in a bimanual movement is important in order to recognise the meaning of the movement. Hand tracking and gesture recognition have been widely addressed in the literature [1]. Spatio temporal hand gesture recognition [2] hidden Markov models for gesture recognition [3] parametric hidden Markov models [4] HMM based threshold models for gesture recognition [5] position based gesture recognition [6] tracking interacting hands using Bayesian networks [7] tracking of ....

Cipolla, R., Pentland, A.: Computer Vision for Human-Machine Interaction. Cambridge University Press (1998)

....section discusses the related literature, and emphasizes the areas in which this paper innovates. Gesture recognition: Much work has been done on gesture recognition over the years, and this section does not attempt a full literature review, but rather points to some prototypical systems. See [7, 14] for reviews. Stamer et al. [17] describe a system which demonstrates impressive results by combining an extremely spartan representation of shape (sixteen measurements based on moments of inertia of the region within the silhouette) with a hidden Markov model of sign transitions. The system can ....

R. Cipolla and A. Pentland. Computer Vision for Human Machine Interaction. Cambridge University Press, 1998.

....Models (HMMs) are presented. The experimental results demonstrate that our method is close to realizing statistics of tennis games automatically using ordinary TV broadcast videos. 1. INTRODUCTION Computer using cameras to observe and interact with their environment is no longer just a fantasy [4]. The most important part for the interaction is the recognition people activities. This problem is addressed in this paper. In general, to be able to completely understand their environment computers need to achieve visual competence near the level of a human being. This is still far beyond the ....

R. Cipolla, A. Pentland eds., Computer Vision for Human-Machine Interaction, Cambridge University Press, 1998.

....first frame (no appearance model is previously learned) and after that the method is fully automatic. In this paper we focus on the application of face modeling. Most of the previous work on face tracking and modeling is focused on generic trackers, which are independent of the person s identity [5,9,10,23,24]. In particular, appearance based face trackers [10,26, 34] make use of PCA in order to construct a linear model of the face s subspace (variation across people) rather than the intra person variations due to changes in expression. When working with person specific models [15,17,20,23] PCA will ....

R. Cipolla and A. Pentland. Computer vision for Human-Machine Interaction. Cambridge university press, 1998.

....problem. In this paper a new algorithm is proposed for the recognition of occluded and non occluded hand gestures based on matching the graphs of gestures in an eigenspace. 1. Introduction The use of hand gesture recognition in Human Computer Interaction has been addressed in the literature. [1] It is a more natural way compared with the use of keyboards, mice, etc. Current approaches to the recognition of hand gesture are often based on statistical methods to extract the features of different shapes of hand in a sequence of images. However, many other different approaches have been ....

R. Cipolla and A. Pentland, Computer Vision for Human-Machine Interaction, Cambridge University Press, 1998.

....Most research into visual gesture recognition focuses on recognising the high level, complex gestures that humans use in real life to communicate with each other. This is an ambitious aim and although considerable results have been achieved in this direction (see, for example, the reviews: [4] [9] 10] and among other papers: 7] 14] it is not the aim of this paper. The computing power required to recognise, in real time, complex gestures by no means corresponds to that of the CPUs currently available on portable systems, and the expressive potential of human gestures is by far ....

R. Cipolla and A. Pentland. Computer Vision for Human-Machine Interaction. Cambridge University Press, 1998.

....are a very attractive domain of investigation due to both the exciting research challenges and the importance and breadth of possible applications. It is strongly influencing recent research in computer vision [1] Realization of such spaces requires innovations not only in the computer vision [2, 3, 4, 5], but also in audio speech processing and analysis [6, 7] and in the multimodal interactive systems area [8, 9, 10] In this paper, we describe the system that handles multiperson interactions in an intelligent meeting room Figure 1. It is being developed and evaluated in a multipurpose ....

R. Cipolla, A. Pentland (editors), Computer Vision for Human-Machine Interaction, Cambridge University Press, Cambridge, UK, 1998

....natural gaze behavior, glancing in each person s direction on a regular basis. Future versions of the kiosk will include speech processing and face detection and recognition. There is currently a great deal of interest in vision and speech based userinterfaces (see the recent collections [6, 8]) We believe the Smart Kiosk to be representative of a broad class of emerging applications in surveillance, autonomous agents, and intelligent vehicles and rooms. A key attribute of the Smart Kiosk application is the real time processing and generation of multimedia data. Video and speech ....

R. Cipolla and A. Pentland, editors. Computer Vision for Human-Machine Interaction. Cambridge University Press, 1998. In press.

....natural gaze behavior, glancing in each person s direction on a regular basis. Future versions of the kiosk will include speech processing and face detection and recognition. There is currently a great deal of interest in vision and speech based userinterfaces (see the recent collections [6, 8]) We believe the Smart Kiosk to be representative of a broad class of emerging applications in surveillance, autonomous agents, and intelligent vehicles and rooms. 2.1 Computational Properties A key attribute of the Smart Kiosk application is the real time processing and generation of ....

Roberto Cipolla and Alex Pentland, editors. Computer Vision for HumanMachine Interaction. Cambridge University Press, 1998.

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R. Cipolla, A. Pentland, Computer Vision for Human--Machine Interaction, Cambridge University Press, Cambridge, 1998.

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R. Cipolla and A. Pentland, Eds., Computer Vision for Human--Machine Interaction. Cambridge, MA: Cambridge Univ. Press, 1998.

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R. Cipolla and A. Pentland. Computer Vision for Human Machine Interaction. Cambridge University Press, 1998.

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R. Cipolla, A. Pentland, Computer Vision for Human--Machine Interaction, Cambridge University Press, Cambridge, 1998.

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R. Cipolla and A. Pentland. Computer Vision for Human Machine Interaction. Cambridge University Press, 1998.

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Cipolla, R. and Pentland A. (ed.) Computer Vision for Human-Machine Interaction, Cambridge University Press, 1998.

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Cipolla, R. and Pentland, A. Computer Vision for HumanMachine Interaction. Cambridge University Press, New York, 1998.

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