Title
A Coupled Discriminative Dictionary and Transformation Learning Approach with Applications to Cross Domain Matching
Abstract
The proposed approach addresses the problem of cross domain / cross modal matching.An objective function to model the relationship between the data from cross-domains.Optimization procedure for solving the objective function.Explicit discriminative term for improved classification performance.Extensive experiments on five datasets and comparisons with state-of-the-art methods. Display Omitted Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach.
Year
DOI
Venue
2016
10.1016/j.patrec.2015.12.003
Pattern Recognition Letters
Keywords
Field
DocType
Face recognition,Activity recognition,Dictionary learning,Metric learning
Computer vision,Facial recognition system,Activity recognition,Dictionary learning,Pattern recognition,Computer science,Action recognition,Artificial intelligence,Transformation matrix,Discriminative model,Modal,Machine learning
Journal
Volume
Issue
ISSN
71
C
0167-8655
Citations 
PageRank 
References 
0
0.34
41
Authors
2
Name
Order
Citations
PageRank
sivaram prasad mudunuri1233.06
Soma Biswas240928.08