1. Machine vision methods for analyzing social interactions
- Author
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Kristin Branson, S.E. Roian Egnor, Alice A. Robie, and Kelly M. Seagraves
- Subjects
0301 basic medicine ,Physiology ,Computer science ,Machine vision ,Video Recording ,Aquatic Science ,Machine learning ,computer.software_genre ,Machine Learning ,03 medical and health sciences ,0302 clinical medicine ,Animals ,Animal behavior ,Social Behavior ,Molecular Biology ,Ecology, Evolution, Behavior and Systematics ,Focus (computing) ,Behavior, Animal ,business.industry ,Scale (chemistry) ,Equipment Design ,Resolution (logic) ,030104 developmental biology ,Quantitative analysis (finance) ,Insect Science ,Animal Science and Zoology ,Artificial intelligence ,business ,computer ,Algorithms ,030217 neurology & neurosurgery ,Social behavior - Abstract
Recent developments in machine vision methods for automatic, quantitative analysis of social behavior have immensely improved both the scale and level of resolution with which we can dissect interactions between members of the same species. In this paper, we review these methods, with a particular focus on how biologists can apply them to their own work. We discuss several components of machine vision-based analyses: methods to record high-quality video for automated analyses, video-based tracking algorithms for estimating the positions of interacting animals, and machine learning methods for recognizing patterns of interactions. These methods are extremely general in their applicability, and we review a subset of successful applications of them to biological questions in several model systems with very different types of social behaviors.
- Published
- 2017
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