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Real-time motion control using pose space probability density estimation

Okwechime, D, Ong, E-J and Bowden, R (2009) Real-time motion control using pose space probability density estimation In: ICCV 2009, 2009-09-29 - 2009-10-04, Kyoto, Japan.

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Abstract

We introduce a new algorithm for real-time interactive motion control and demonstrate its application to motion captured data, pre-recorded videos and HCI. Firstly, a data set of frames are projected into a lower dimensional space. An appearance model is learnt using a multivariate probability distribution. A novel approach to determining transition points is presented based on k-medoids, whereby appropriate points of intersection in the motion trajectory are derived as cluster centres. These points are used to segment the data into smaller subsequences. A transition matrix combined with a kernel density estimation is used to determine suitable transitions between the subsequences to develop novel motion. To facilitate real-time interactive control, conditional probabilities are used to derive motion given user commands. The user commands can come from any modality including auditory, touch and gesture. The system is also extended to HCI using audio signals of speech in a conversation to trigger non-verbal responses from a synthetic listener in real-time. We demonstrate the flexibility of the model by presenting results ranging from data sets composed of vectorised images, 2D and 3D point representations. Results show real-time interaction and plausible motion generation between different types of movement.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
NameEmailORCID
Okwechime, DUNSPECIFIEDUNSPECIFIED
Ong, E-JUNSPECIFIEDUNSPECIFIED
Bowden, RUNSPECIFIEDUNSPECIFIED
Date : 2009
Identification Number : 10.1109/ICCVW.2009.5457534
Contributors :
ContributionNameEmailORCID
http://www.loc.gov/loc.terms/relators/PBLIEEE, UNSPECIFIEDUNSPECIFIED
Additional Information : Copyright 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Depositing User : Symplectic Elements
Date Deposited : 28 Mar 2017 14:42
Last Modified : 31 Oct 2017 14:33
URI: http://epubs.surrey.ac.uk/id/eprint/531469

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