Pedestrian counting and detection at a traffic intersection based on location of vehicle zones

摘要

Pedestrian detection and counting for traffic intersection control analyzes characteristics of a field of view of a traffic detection zone to determine a location and size of a pedestrian area, and applies protocols for evaluating pixel content in the field of view to identify individual pedestrians. The location and size of a pedestrian area is determined based either on locations of vehicle and bicycle detection areas or on movement of various objects within the field of view. Automatic pedestrian speed calibration with a region of interest for pedestrian detection is accomplished using lane and other intersection markings in the field of view. Detection and counting further includes identifying a presence, volume, velocity and trajectory of pedestrians in the pedestrian area of the traffic detection zone.

主权项

1. A method, comprising:
receiving input data representing a field of view of a traffic detection zone; analyzing the input data within a computing environment in one or more data processing modules executed in conjunction with at least one specifically-configured processor, the one or more data processing modules configured to a) identify a region in the field of view of the traffic detection zone used by one or more pedestrians, and b) accurately count the one or more pedestrians in the traffic detection zone, by
1) determining a pedestrian zone in the field of view, by a) identifying a position of at least one vehicle detection zone in nearest proximity to a stop bar, each at least one vehicle detection zone having a height that extends to or near to the stop bar, and b) calculating a height of a pedestrian area in the field of view from the height of the at least one vehicle detection zone;2) counting the one or more pedestrians in the pedestrian zone by, a) analyzing portions of the pedestrian zone in the field of view, b) computing features of current pixel content identified in the analyzed portions by identifying part-based features defining an individual pedestrian that include one or more of body structure combinations, body shape, body width or walking gestures, c) developing a model of a single walking pedestrian to separate each individual pedestrian in a group of moving pedestrians in the field of view, by computing pedestrian features using pixels defining a pedestrian contour, d) determining a matching confidence between an individual pedestrian and a group of moving pedestrians by calculating a mathematical similarity between the computed features of current pixel content and the model of the single walking pedestrian, and e) incrementing a pedestrian count where a high matching confidence indicates that an individual pedestrian has been identified; and generating, as output data, the pedestrian count.