计算机科学
视频跟踪
软件
领域(数学)
计算机视觉
接口(物质)
对象(语法)
跟踪(教育)
实时计算
人工智能
人机交互
最大气泡压力法
纯数学
程序设计语言
并行计算
气泡
数学
教育学
心理学
作者
Jon Patman,Sabrina Michael,Marvin M. F. Lutnesky,Kannappan Palaniappan
标识
DOI:10.1109/aipr.2018.8707411
摘要
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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