Crowd behavior analysis: A review where physics meets biology

•Review crowd behavior studies in computer vision from physics and biology outlooks.•Overview of the key attributes of crowd from the perspectives of the two sciences.•General attributes of crowd: decentralized, collective motion, emergent behavior.•Contradicting attributes of crowd: thinking/non-thinking, bias/non-bias.•Discuss sample applications of crowd based on attributes and benchmarked datasets.

Although the traits emerged in a mass gathering are often non-deliberative, the act of mass impulse may lead to irrevocable crowd disasters. The two-fold increase of carnage in crowd since the past two decades has spurred significant advances in the field of computer vision, towards effective and proactive crowd surveillance. Computer vision studies related to crowd are observed to resonate with the understanding of the emergent behavior in physics (complex systems) and biology (animal swarm). These studies, which are inspired by biology and physics, share surprisingly common insights, and interesting contradictions. However, this aspect of discussion has not been fully explored. Therefore, this survey provides the readers with a review of the state-of-the-art methods in crowd behavior analysis from the physics and biologically inspired perspectives. We provide insights and comprehensive discussions for a broader understanding of the underlying prospect of blending physics and biology studies in computer vision.