Touching-Pigs Segmentation using Concave Points in Continuous Video Frames

Abstract

Caring individual pigs in large-scale pig farms is an important issue for preventing infectious diseases. Accordingly, many researchers have been researched about group-housed pig monitoring systems. However, it is challenging to identify individual pigs because the systems misidentify touching-pigs as a single pig. In this paper, we solve the touching-pig problem by using concave points of continuous video frames. We interpret a two dimensional outline data as a one dimensional time-series data of touching pigs and align the time-series data of continuous video frames. The experimental results show that the proposed method can segment the touching-pigs more accurate than generally used methods in real time.