Crowd Scene Understanding from Video

Abstract

Crowd video analysis has applications in crowd management, public space design, and visual surveillance. Example tasks potentially aided by automated analysis include anomaly detection (such as a person walking against the grain of traffic or rapid assembly/dispersion of groups of people), population and density measurements, and interactions between groups of people. This survey explores crowd analysis as it relates to two primary research areas: crowd statistics and behavior understanding. First, we survey methods for counting individuals and approximating the density of the crowd. Second, we showcase research efforts on behavior understanding as related to crowds. These works focus on identifying groups, interactions within small groups, and abnormal activity detection such as riots and bottlenecks in large crowds. Works presented in this section also focus on tracking groups of individuals, either as a single entity or a subset of individuals within the frame of reference. Finally, a summary of datasets available for crowd activity video research is provided.

Intelligent video surveillance: a review through deep learning techniques for crowd analysis

“…Crowd Scene Understanding from Video A survey [86] mainly deals with crowd counting. Different approaches for crowd counting are categorized into six.…”

“…Crowd scene understanding from video: a survey [86] 2017 ACM literature review. Finally the vital points which need more consideration in near future are explicitly stated.…”

A Multitask Cascading CNN with MultiScale Infrared Optical Flow Feature Fusion-Based Abnormal Crowd Behavior Monitoring UAV

“…With the increase of population and diversity of human activities in recent years, crowd analyses and estimates from videos [ 1 , 2 ]—which have been more frequent in the real world than ever before—have recently attracted increasing interest from the computer vision research community and have become an active research topic, with many applications in maintaining safety and social stability in public places [ 3 , 4 ], intelligent video surveillance [ 5 , 6 ], etc. In the real world, temporary large-scale venues present larger challenges to traditional fixed-video monitoring systems.…”

“…In the monitoring of public areas, due to the unpredictability of dangerous types and the complexity of crowd movement, various abnormal crowd events may occur. For different scenarios, abnormal behavior has different manifestations and lack a strict definition [ 2 , 5 ]. Abnormal crowd events can be divided into (1) abnormal individual events and (2) abnormal group events.…”

“…Many researchers have focused on single-pedestrian detection [ 13 , 14 , 15 ], crowd counting and analysis [ 3 , 5 , 6 , 16 , 17 , 18 ] and UAV-based computer-vision applications.…”