A Probabilistic Framework for Matching Temporal Trajectories: CONDENSATION-Based Recognition of Gestures and Expressions
نویسندگان
چکیده
The recognition of human gestures and facial expressions in image sequences is an important and challenging problem that enables a host of human-computer interaction applications. This paper describes a framework for incremental recognition of human motion that extends the “Condensation” algorithm proposed by Isard and Blake (ECCV’96). Human motions are modeled as temporal trajectories of some estimated parameters over time. The Condensation algorithm uses random sampling techniques to incrementally match the trajectory models to the multi-variate input data. The recognition framework is demonstrated with two examples. The first example involves an augmented office whiteboard with which a user can make simple hand gestures to grab regions of the board, print them, save them, etc. The second example illustrates the recognition of human facial expressions using the estimated parameters of a learned model of mouth motion.
منابع مشابه
Gesture recognition using a probabilistic framework for pose matching
This paper presents an approach for view-based recognition of gestures. The approach is based on representing each gesture as a sequence of learned body poses. The gestures are recognized through a probabilistic framework for matching these body poses and for imposing temporal constrains between different poses. Matching individual poses to image data is performed using a probabilistic formulat...
متن کاملTwo Hand Dynamic Gesture Recognition Using Random Sampling Techniques
This work develops a framework for recognition of two hand dynamic gestures, using condensation algorithm. The work is broadly divided into three parts. First part of this work deals with skin color identification using color segmentation using' Gaussian Mixture Model'. In the Second part hand motions are modeled as trajectories of some estimated parameters over time. During training, one templ...
متن کاملRecognizing Temporal Trajectories Using the Condensation Algorithm
The recognition of human gestures in image sequences is an important and challengingproblem that enables a host of human-computer interaction applications. This paper describes an incremental recognition strategy that is an extension of the “Condensation” algorithm proposed by Isard and Blake (ECCV’96). Gestures are modeled as temporal trajectories of some estimated parameter over time (in this...
متن کاملStatistical Gesture Recognition throughModelling of Parameter
The recognition of human gestures is a challenging problem that can contribute to a natural man{machine interface. In this paper, we present a new technique for gesture recognition. Gestures are modelled as temporal trajectories of parameters. Local sub-sequences of these trajectories are extracted and used to deene an orthogonal space using principal component analysis. In this space the proba...
متن کامل