UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Constrained mutual convex cone method for image set based recognition

Sogi, N; Zhu, R; Xue, J-H; Fukui, K; (2022) Constrained mutual convex cone method for image set based recognition. Pattern Recognition , 121 , Article 108190. 10.1016/j.patcog.2021.108190. Green open access

[thumbnail of NaoyaSogi-PR-2021-accepted.pdf]
Preview
Text
NaoyaSogi-PR-2021-accepted.pdf - Accepted Version

Download (1MB) | Preview

Abstract

In this paper, we propose convex cone-based frameworks for image-set classification. Image-set classification aims to classify a set of images, usually obtained from video frames or multi-view cameras, into a target object. To accurately and stably classify a set, it is essential to accurately represent structural information of the set. There are various image features, such as histogram-based features and convolutional neural network features. We should note that most of them have non-negativity and thus can be effectively represented by a convex cone. This leads us to introduce the convex cone representation to image-set classification. To establish a convex cone-based framework, we mathematically define multiple angles between two convex cones, and then use the angles to define the geometric similarity between them. Moreover, to enhance the framework, we introduce two discriminant spaces. We first propose a discriminant space that maximizes gaps between cones and minimizes the within-class variance. We then extend it to a weighted discriminant space by introducing weights on the gaps to deal with complicated data distribution. In addition, to reduce the computational cost of the proposed methods, we develop a novel strategy for fast implementation. The effectiveness of the proposed methods is demonstrated experimentally by using five databases.

Type: Article
Title: Constrained mutual convex cone method for image set based recognition
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.patcog.2021.108190
Publisher version: http://dx.doi.org/10.1016/j.patcog.2021.108190
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Image-set based method, Convex cone representation, Multiple angles
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/10132000
Downloads since deposit
14Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item