Title
Exploiting transfer learning for personalized view invariant gesture recognition
Abstract
A robust gesture recognition system is an essential component in many human-computer interaction applications. In particular, the widespread adoption of portable devices and the diffusion of autonomous systems with limited power and load capacity has increased the need of developing efficient recognition algorithms which operates on video streams recorded from low cost devices and which can cope with the challenging issue of point of view changes. A further challenge arises as different users tend to perform the same gesture with different styles and speeds. Thus a classifier trained with gestures data of certain set of users may work poorly when data from other users are being processed. However, as often a mobile device or a robot are intended to be used by a single or by a small group of people, it would be desirable to have a gesture recognition system designed specifically for these users. In this paper we introduce a novel approach to face the problems of view-invariance and user personalization in the context of gesture interaction systems. More specifically, we propose a domain adaptation framework based on a feature space augmentation approach operating on robust view-invariant Self Similarity Matrix descriptors. To prove the effectiveness of our method a dataset corresponding to 17 users performing 10 different gestures under 3 point of views is collected and an extensive experimental evaluation is performed.
Year
DOI
Venue
2014
10.1109/ICASSP.2014.6853797
Acoustics, Speech and Signal Processing
Keywords
Field
DocType
gesture recognition,human computer interaction,mobile robots,video streaming,domain adaptation framework,feature space augmentation,gesture interaction systems,human-computer interaction,mobile device,mobile robot,personalized view invariant gesture recognition,portable devices,robust gesture recognition,self similarity matrix descriptors,transfer learning,user personalization,video streams,Gesture recognition,low cost cameras,transfer learning,view invariance
Self-similarity matrix,Computer science,Gesture,Gesture recognition,Human–computer interaction,Artificial intelligence,Personalization,Computer vision,Interaction technique,Feature vector,Pattern recognition,Sketch recognition,Mobile device
Conference
ISSN
Citations 
PageRank 
1520-6149
0
0.34
References 
Authors
16
4
Name
Order
Citations
PageRank
Gabriele Costante18111.40
Galieni, V.200.34
Yan Yan369131.13
Fravolini, M.L.4143.04