Person detection in hyperspectral images via skin segmentation using an active learning approach

Ion Marqués; Manuel Graña; Stephanie M. Sanchez; Mohammed Q. Alkhatib; Miguel Velez-Reyes

doi:10.1117/12.2179333

21 May 2015 Person detection in hyperspectral images via skin segmentation using an active learning approach

Ion Marqués, Manuel Graña, Stephanie M. Sanchez, Mohammed Q. Alkhatib, Miguel Velez-Reyes

Proceedings Volume 9472, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI; 947207 (2015) https://doi.org/10.1117/12.2179333
Event: SPIE Defense + Security, 2015, Baltimore, MD, United States

Abstract

Human skin detection is a computer vision problem that has been widely researched in color images. In this article we deal with this task as an interactive segmentation problem in hyperspectral outdoor images. We have focused on the problem of skin identification in hyperspectral cameras allowing a fine sampling of the light spectrum, so that the information gathered at each pixel is a high dimensional vector. The problem is treated as a classification problem, where we make use of active learning strategies to provide an interactive robust solution reaching high accuracy in a short training/testing cycle.

Citation Download Citation

Ion Marqués, Manuel Graña, Stephanie M. Sanchez, Mohammed Q. Alkhatib, and Miguel Velez-Reyes "Person detection in hyperspectral images via skin segmentation using an active learning approach", Proc. SPIE 9472, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXI, 947207 (21 May 2015); https://doi.org/10.1117/12.2179333

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KEYWORDS

Image segmentation

Reflectivity

Skin

Hyperspectral imaging

Image processing

Cameras

Error analysis

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