BioSense:动物运动和行为研究的实时目标跟踪

Jon Patman, Sabrina C. J. Michael, Marvin M. F. Lutnesky, K. Palaniappan
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引用次数: 11

摘要

视频目标跟踪已经在从自动驾驶汽车导航到医学图像分析的众多应用中获得了巨大的成功。基于自动视频的动物行为理解是一个广泛而新兴的探索领域。有趣的,但难以验证的假设,可以通过高通量处理从实验室和现场实验收集的动物运动和相互作用来评估。在本文中,我们描述了BioSense,一个新的独立软件平台和用户界面,为研究人员提供了一个开源框架,用于收集和定量分析表征动物运动和行为的视频数据(例如空间位置,速度,区域偏好等)。BioSense能够实时跟踪多个物体,使用适用于各种环境和动物的各种物体检测方法。实时操作还提供了一种战术方法的对象跟踪,允许用户能够操纵软件的控制,同时立即看到视觉反馈。我们在一系列视频跟踪基准中评估了BioSense的能力,这些基准代表了动物行为研究中存在的挑战。
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BioSense: Real-Time Object Tracking for Animal Movement and Behavior Research
Video object tracking has been used with great success in numerous applications ranging from autonomous vehicle navigation to medical image analysis. A broad and emerging domain for exploration is in the field of automatic video-based animal behavior understanding. Interesting, yet difficult-to-test hypotheses, can be evaluated by high-throughput processing of animal movements and interactions collected from both laboratory and field experiments. In this paper we describe BioSense, a new standalone software platform and user interface that provides researchers with an open-source framework for collecting and quantitatively analyzing video data characterizing animal movement and behavior (e.g. spatial location, velocity, region preference, etc.). BioSense is capable of tracking multiple objects in real-time, using various object detection methods suitable for a range of environments and animals. Real-time operation also provides a tactical approach to object tracking by allowing users the ability to manipulate the control of the software while seeing visual feedback immediately. We evaluate the capabilities of BioSense in a series of video tracking benchmarks representative of the challenges present in animal behavior research.
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