Traffic flow detection method based on object detection

Abstract

The invention provides a traffic flow detection method based on object detection and belongs to the technical field of intelligent video monitoring. At present, traffic flow detection has the problem that effective division is hard to perform on power-driven vehicles or non-power-driven vehicles. The traffic flow detection method based on the object detection includes: firstly a real-time object detector based on random ferns is obtained through off-line training, then object detection is performed on traffic video images through the real-time object detector, types and quantity of objects in the current video scene are determined, mark matching based on an active region is performed on a detection result during operation, and calculation on traffic flow is achieved. Simultaneously, through adding of a novel training data on-line updating detector, the traffic flow detection method based on the object detection enables a system to be optimized and perfected continuously, can perform real-time classified calculation and statistics on the traffic flow, enables flow calculation results to be accurate, and is mainly used for traffic flow detection.

Description

technical field [0001] The invention belongs to the technical field of intelligent video monitoring, in particular to the technical field of computer graphics and image processing. Background technique [0002] Traffic flow detection is an important basic work of intelligent transportation system. It provides an important data source for intelligent traffic management and control, and is widely used in traffic guidance, road resource allocation, road construction evaluation and other fields. Compared with traditional permanently embedded detection based on piezoelectric circuits (such as annular buried coil detection) and suspended detection (such as detection based on closed-circuit television, microwave, radar, infrared or ultrasonic sensors), the method of video image detection has the advantages of Obvious advantages: large detection coverage, multiple detection parameters; simple installation, convenient maintenance; no damage to the road surface, low engineering cost, ...

AI Technical Summary

Problems solved by technology

This fixed window detection method often causes false detection when the vehicle changes lanes or vehicles in adjacent lanes partially cover the detection window of the detected lane.

In addition, a common problem of these methods is that they cannot effectively distinguish vehicles, and it is difficult to take non-motorized vehicles into flow calculation

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