Loitering Detection Based on Pedestrian Activity Area Classification

Abstract

Loitering detection can help recognize vulnerable people needing attention and potential suspects harmful to public security. The existing loitering detection methods used time or target trajectories as assessment criteria, and only handled some simple loitering circumstances because of complex track. To solve these problems, this paper proposes a loitering detection method based on pedestrian activity area classification. The paper first gave loitering definition from a new perspective using the size of pedestrian activity area. The pedestrian loitering behaviors were divided into three categories. The proposed algorithms dynamically calculate enclosing rectangle, ellipse, and sector of pedestrian activity areas through curve fitting based on trajectory coordinates within given staying time threshold. The loitering is recognized if the pedestrian activity is detected to be constrained in an area within a certain period of time. The algorithm does not need to calculate complex trajectories. The PETS2007 dataset and our own self-collected simulated test videos were tested. The experimental results show that the proposed method accurately detected the pedestrian loitering, not only detected some loitering that the existing methods could not detect, but also distinguishing different types of loitering. The proposed method is effectiveness, robust, and simplified in implementation.

Abnormal Behavior Detection in Uncrowded Videos with Two-Stream 3D Convolutional Neural Networks

“…Their system monitors the individuals and applies a Generalized Sequential Patterns (GSP) algorithm to detect predefined patterns of repeated actions that characterize loitering. Huang et al [14] have proposed an approach that detects loitering based on pedestrian activity area fitting within three categories i.e., rectangle, ellipse, and sector loitering. The type of loitering is determined by trajectory maps and analyzing the suspicious target trajectory.…”

“…Similarly, concerning movement type, Huang et al [14] have found loitering to be a case of movement that forms a certain motion trajectory within a specific activity area. In this way, the following cases are possible: i.…”

“…Loitering detection is critical as it can help to identify the cases where (i) vulnerable people such as older patients with Alzheimer's disease need attention, and (ii) potential suspects involved in illegal activity are noticed [14]. Different studies (e.g., [14,16]) have defined the act of loitering based on two main characteristics. First, loitering is the act of lingering in a certain area for more than a specified time.…”

“…They have reported the precision and recall values of 87% and 53%, respectively, on Caviar-DS. Huang et al [14] have presented a method based on pedestrian activity area classification. They divided the loitering behaviors into three categories, namely rectangle, ellipse, and sector loitering.…”

“…Loitering can be defined as the act of being in a specific public space for a given period with no clear objective. Some examples of the works in this category include [14][15][16]. In contrast, when a few people are involved instead of one person in the uncrowded scene, identifying violent behavior, such as fighting, kicking, and punching between two people, becomes intriguing.…”