Depth-Based Detection of Standing-Pigs in Moving Noise Environments
AbstractIn 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
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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.
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(12):2757.Chicago/Turabian Style
Kim, Jinseong; Chung, Yeonwoo; Choi, Younchang; Sa, Jaewon; Kim, Heegon; Chung, Yongwha; Park, Daihee; Kim, Hakjae. 2017. "Depth-Based Detection of Standing-Pigs in Moving Noise Environments." Sensors 17, no. 12: 2757.
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