Wild Animal Recognition Method for Videos Using a Combination of Deep Learning and Motion Detection

中島 彩奈, 奥 浩之, 茂木 和弘, 白石 洋一
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引用次数: 3

Abstract

This paper proposes a new wildlife image recognition method that combines object recognition based on deep learning and motion detection by inter-frame difference. This method makes it possible that such animal images as difficult to detect by object recognition can be detected by motion detection, and vice versa. The experimental results show the detection ratio and hit ratio are 100% and 84%, respectively, for videos including animals. Our achieved results can provide more efficient solutions for the time consuming and costly mitigation approaches to reduce human-wildlife conflicts.
基于深度学习和运动检测的视频野生动物识别方法
本文提出了一种将基于深度学习的目标识别和帧间差分运动检测相结合的野生动物图像识别新方法。这种方法使得难以通过物体识别检测到的动物图像可以通过运动检测检测到,反之亦然。实验结果表明,对于包含动物的视频,该方法的检测率为100%,命中率为84%。我们取得的成果可以为减少人类与野生动物冲突的耗时和昂贵的缓解办法提供更有效的解决办法。
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