Collaborative Descriptors: Convolutional Maps for Preprocessing

Hirokatsu Kataoka; Kaori Abe; Akio Nakamura; Yutaka Satoh

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arXiv · 1705.03595

Collaborative Descriptors: Convolutional Maps for Preprocessing

Hirokatsu Kataoka·Kaori Abe·Akio Nakamura·Yutaka Satoh

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Abstract

The paper presents a novel concept for collaborative descriptors between deeply learned and hand-crafted features. To achieve this concept, we apply convolutional maps for pre-processing, namely the convovlutional maps are used as input of hand-crafted features. We recorded an increase in the performance rate of +17.06 % (multi-class object recognition) and +24.71 % (car detection) from grayscale input to convolutional maps. Although the framework is straight-forward, the concept should be inherited for an improved representation.

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Hirokatsu Kataoka, Kaori Abe, Akio Nakamura, Yutaka Satoh. 2017-05-10. Collaborative Descriptors: Convolutional Maps for Preprocessing. https://arxiv.org/abs/1705.03595

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