Triplet Transform Learning for Automated Primate Face Recognition

doi:10.1109/ICIP.2019.8803501

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Triplet Transform Learning for Automated Primate Face Recognition

Proceedings Article•DOI•

Triplet Transform Learning for Automated Primate Face Recognition

Mohit Agarwal¹, Sanchit Sinha¹, Maneet Singh¹, Shruti Nagpal¹, Richa Singh¹, Mayank Vatsa¹ - Show less +3 more•Institutions (1)

Indraprastha Institute of Information Technology¹

01 Sep 2019-pp 3462-3466

TL;DR: A novel Triplet Transform Learning (TTL) model for learning discriminative representations of primate faces is proposed, where it outperforms the existing approaches and attains state-of-the-art performance on the primates database.

Abstract: Automated primate face recognition has enormous potential in effective conservation of species facing endangerment or extinction. The task is characterized by lack of training data, low inter-class variations, and large intra-class differences. Owing to the challenging nature of the problem, limited research has been performed to automate the process of primate face recognition. In this research, we propose a novel Triplet Transform Learning (TTL) model for learning discriminative representations of primate faces. The proposed model reduces the intra-class variations and increases the inter-class variations to obtain robust sparse representations for the primate faces. It is utilized to present a novel framework for primate face recognition, which is evaluated on the primate dataset, comprising of 80 identities including monkeys, gorillas, and chimpanzees. Experimental results demonstrate the efficacy of the proposed approach, where it outperforms the existing approaches and attains state-of-the-art performance on the primates database.

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"Triplet Transform Learning for Auto..." refers methods in this paper

...In the proposed framework, two separate transforms are learned for the VGG-Face and LCNN features, respectively....
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...3, the proposed framework utilizes the TTL model with features extracted from the VGG-Face [15] and Light-CNN (LCNN) [16] architectures....
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...Analysis of the Proposed Framework: The effectiveness of the TTL model can be observed by comparing the perfor- mance of VGG-Face (LCNN)+Cosine distance with VGGFace (LCNN)+TTL+Cosine distance (Table 1)....
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...Further, the proposed framework demonstrates an improvement of around 6% as compared to independent VGGFace/LCNN+TTL+Cosine distance performance, thereby strengthening the inclusion of score-level fusion in the recognition pipeline....
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...VGG-Face and LCNN are recent CNN architectures which have shown to perform well for face recognition, having the penultimate layer dimension as 4096 and 256, respectively....
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