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Sensors 2017, 17(12), 2757;

Depth-Based Detection of Standing-Pigs in Moving Noise Environments

Department of Computer and Information Science, Korea University, Sejong City 30019, Korea
Department of Applied Statistics, Korea University, Sejong City 30019, Korea
Class Act Co., Ltd., Digital-ro, Geumcheon-gu, Seoul 08589, Korea
Author to whom correspondence should be addressed.
Received: 30 October 2017 / Revised: 24 November 2017 / Accepted: 27 November 2017 / Published: 29 November 2017
(This article belongs to the Special Issue Imaging Depth Sensors—Sensors, Algorithms and Applications)
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In a surveillance camera environment, the detection of standing-pigs in real-time is an important issue towards the final goal of 24-h tracking of individual pigs. In this study, we focus on depth-based detection of standing-pigs with “moving noises”, which appear every night in a commercial pig farm, but have not been reported yet. We first apply a spatiotemporal interpolation technique to remove the moving noises occurring in the depth images. Then, we detect the standing-pigs by utilizing the undefined depth values around them. Our experimental results show that this method is effective for detecting standing-pigs at night, in terms of both cost-effectiveness (using a low-cost Kinect depth sensor) and accuracy (i.e., 94.47%), even with severe moving noises occluding up to half of an input depth image. Furthermore, without any time-consuming technique, the proposed method can be executed in real-time. View Full-Text
Keywords: agriculture IT; computer vision; foreground detection; depth information; moving noise agriculture IT; computer vision; foreground detection; depth information; moving noise

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Kim, J.; Chung, Y.; Choi, Y.; Sa, J.; Kim, H.; Chung, Y.; Park, D.; Kim, H. Depth-Based Detection of Standing-Pigs in Moving Noise Environments. Sensors 2017, 17, 2757.

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