Robust Tracking and Behavioral Modeling of Movements of Biological Collectives from Ordinary Video Recordings

Autor:	Sayama, Hiroki, Esfahlani, Farnaz Zamani, Jazayeri, Ali, Turner, J. Scott
Rok vydání:	2017
Předmět:	Computer Science - Multiagent Systems Computer Science - Computer Vision and Pattern Recognition Nonlinear Sciences - Adaptation and Self-Organizing Systems Quantitative Biology - Quantitative Methods
Druh dokumentu:	Working Paper
Popis:	We propose a novel computational method to extract information about interactions among individuals with different behavioral states in a biological collective from ordinary video recordings. Assuming that individuals are acting as finite state machines, our method first detects discrete behavioral states of those individuals and then constructs a model of their state transitions, taking into account the positions and states of other individuals in the vicinity. We have tested the proposed method through applications to two real-world biological collectives: termites in an experimental setting and human pedestrians in a university campus. For each application, a robust tracking system was developed in-house, utilizing interactive human intervention (for termite tracking) or online agent-based simulation (for pedestrian tracking). In both cases, significant interactions were detected between nearby individuals with different states, demonstrating the effectiveness of the proposed method. Comment: 8 pages, 14 figures; to be published in the Proceedings of the IEEE SSCI 2017
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1707.07310 Zobrazit plný text záznamu View this record from Arxiv