Learning-based dynamic coupling of discrete and continuous trackers

Authors:
Gabriel Tsechpenakis;Dimitris Metaxas;Carol Neidle
Affiliations:
Center for Computational Biomedicine, Imaging and Modeling (CBIM), Computer Science Department, Rutgers University, Piscataway, NJ;Center for Computational Biomedicine, Imaging and Modeling (CBIM), Computer Science Department, Rutgers University, Piscataway, NJ;Linguistics Program, Department of Modern Foreign Languages and Literatures, Boston University, Boston, MA
Venue:
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Year:
2006

Citing 11
Cited 4

A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves

IEEE Transactions on Pattern Analysis and Machine Intelligence
Curvature scale space image in shape similarity retrieval

Multimedia Systems
A framework for recognizing the simultaneous aspects of American sign language

Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
A System for Person-Independent Hand Posture Recognition against Complex Backgrounds

IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-Based Analysis of Hand Posture

IEEE Computer Graphics and Applications
A framework for motion recognition with applications to American sign language and gait recognition

HUMO '00 Proceedings of the Workshop on Human Motion (HUMO'00)
Model-based tracking of self-occluding articulated objects

ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Real-Time 3-D Hand Posture Estimation Based on 2-D Appearance Retrieval Using Monocular Camera

RATFG-RTS '01 Proceedings of the IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (RATFG-RTS'01)
Tracking Articulated Hand Motion with Eigen Dynamics Analysis

ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
3D Tracking = Classification + Interpolation

ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Shape context and chamfer matching in cluttered scenes

CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition

Simultaneous spotting of signs and fingerspellings based on hierarchical conditional random fields and boostmap embeddings

Pattern Recognition
Features extraction from hand images based on new detection operators

Pattern Recognition
Fingerspelling recognition through classification of letter-to-letter transitions

ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
A review of motion analysis methods for human Nonverbal Communication Computing

Image and Vision Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a data-driven dynamic coupling between discrete and continuous methods for tracking objects of high dofs, which overcomes the limitations of previous techniques. In our approach, two trackers work in parallel, and the coupling between them is based on the tracking error. We use a model-based continuous method to achieve accurate results and, in cases of failure, we re-initialize the model using our discrete tracker. This method maintains the accuracy of a more tightly coupled system, while increasing its efficiency. At any given frame, our discrete tracker uses the current and several previous frames to search into a database for the best matching solution. For improved robustness, object configuration sequences, rather than single configurations, are stored in the database. We apply our framework to the problem of 3D hand tracking from image sequences and the discrimination between fingerspelling and continuous signs in American Sign Language.