在野生动物录像中追踪多种动物

David Tweed, A. Calway
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引用次数: 25

摘要

我们描述了一种在野生动物录像中跟踪动物的方法。它使用一个冷凝粒子过滤框架,由特定动物的学习特征驱动。关键贡献是基于重要身体点上可追踪特征随时间的相对位置的动物运动周期模型。我们还介绍了在粒子滤波器中随时间保持多模态密度的技术,以实现对多个动物的一致跟踪。初步实验表明,该方法具有相当大的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tracking multiple animals in wildlife footage
We describe a method for tracking animals in wildlife footage. It uses a CONDENSATION particle filtering frame-work driven by learnt characteristics of specific animals. The key contribution is a periodic model of animal motion based on the relative positions over time of trackable features at significant body points. We also introduce techniques for maintaining a multimodal state density within the particle filter over time to enable consistent tracking of multiple animals. Initial experiments show that the approach has considerable potential.
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