Visual object clustering via mixed-norm regularization

Xin Zhang, Duc-Son Pham, Dinh Phung, Wanquan Liu, Budhaditya Saha, Svetha Venkatesh

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1 Citation (Scopus)

Abstract

Many vision problems deal with high-dimensional data, such as motion segmentation and face clustering. However, these high-dimensional data usually lie in a low-dimensional structure. Sparse representation is a powerful principle for solving a number of clustering problems with high-dimensional data. This principle is motivated from an ideal modeling of data points according to linear algebra theory. However, real data in computer vision are unlikely to follow the ideal model perfectly. In this paper, we exploit the mixed norm regularization for sparse subspace clustering. This regularization term is a convex combination of the l1norm, which promotes sparsity at the individual level and the block norm l2/1 which promotes group sparsity. Combining these powerful regularization terms will provide a more accurate modeling, subsequently leading to a better solution for the affinity matrix used in sparse subspace clustering. This could help us achieve better performance on motion segmentation and face clustering problems. This formulation also caters for different types of data corruptions. We derive a provably convergent algorithm based on the alternating direction method of multipliers (ADMM) framework, which is computationally efficient, to solve the formulation. We demonstrate that this formulation outperforms other state-of-arts on both motion segmentation and face clustering.

Original languageEnglish
Title of host publicationProceedings - IEEE Winter Conference on Applications of Computer Vision - WACV 2015
Subtitle of host publication5–9 January 2015 Waikoloa Beach, Hawaii
EditorsSudeep Sarkar, Subhodev Das, Bahram Parvin, Fatih Porikli
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1030-1037
Number of pages8
ISBN (Electronic)9781479966820
DOIs
Publication statusPublished - 2015
Externally publishedYes
EventIEEE Winter Conference on Applications of Computer Vision 2015 - Waikoloa Beach Marriott Resort & Spa, Big Island, United States of America
Duration: 5 Jan 20159 Jan 2015
http://wacv2015.org/
https://ieeexplore.ieee.org/xpl/conhome/7045624/proceeding (Proceedings)

Conference

ConferenceIEEE Winter Conference on Applications of Computer Vision 2015
Abbreviated titleWACV 2015
CountryUnited States of America
CityBig Island
Period5/01/159/01/15
Internet address

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