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Sensors 2017, 17(5), 1065; doi:10.3390/s17051065

Convolutional Neural Network-Based Human Detection in Nighttime Images Using Visible Light Camera Sensors

Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro 1-gil, Jung-gu, Seoul 100-715, Korea
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Academic Editor: Vittorio M. N. Passaro
Received: 31 March 2017 / Revised: 4 May 2017 / Accepted: 4 May 2017 / Published: 8 May 2017
(This article belongs to the Section Physical Sensors)
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Abstract

Because intelligent surveillance systems have recently undergone rapid growth, research on accurately detecting humans in videos captured at a long distance is growing in importance. The existing research using visible light cameras has mainly focused on methods of human detection for daytime hours when there is outside light, but human detection during nighttime hours when there is no outside light is difficult. Thus, methods that employ additional near-infrared (NIR) illuminators and NIR cameras or thermal cameras have been used. However, in the case of NIR illuminators, there are limitations in terms of the illumination angle and distance. There are also difficulties because the illuminator power must be adaptively adjusted depending on whether the object is close or far away. In the case of thermal cameras, their cost is still high, which makes it difficult to install and use them in a variety of places. Because of this, research has been conducted on nighttime human detection using visible light cameras, but this has focused on objects at a short distance in an indoor environment or the use of video-based methods to capture multiple images and process them, which causes problems related to the increase in the processing time. To resolve these problems, this paper presents a method that uses a single image captured at night on a visible light camera to detect humans in a variety of environments based on a convolutional neural network. Experimental results using a self-constructed Dongguk night-time human detection database (DNHD-DB1) and two open databases (Korea advanced institute of science and technology (KAIST) and computer vision center (CVC) databases), as well as high-accuracy human detection in a variety of environments, show that the method has excellent performance compared to existing methods. View Full-Text
Keywords: intelligent surveillance system; nighttime human detection; visible light image; convolutional neural network intelligent surveillance system; nighttime human detection; visible light image; convolutional neural network
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Kim, J.H.; Hong, H.G.; Park, K.R. Convolutional Neural Network-Based Human Detection in Nighttime Images Using Visible Light Camera Sensors. Sensors 2017, 17, 1065.

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