Real-time Video Triggering for Traffic Surveillance Using Motion Blob Detection
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Solution Overview
Problem
Existing traffic surveillance systems, particularly those using inductive loops, are expensive to install and maintain, and require improved methods for real-time video triggering in traffic surveillance and photo enforcement applications.
Innovation Solution
A method and system for real-time video triggering that involves receiving a streaming video feed, performing spatial uniformity correction when ambient light is low, resampling to a lower spatial resolution, detecting motion blobs using bi-directional frame differences and morphological filtering, and applying a three-layered approach to identify candidate motion blobs, such as license plates, for triggering video collection actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If inductive loops are used for triggering, then triggering capability is provided, but installation and maintenance cost increases
Solution Approach 1:
The patent replaces the mechanical inductive loop system embedded in pavement with an optical-based video camera system that captures images and detects vehicles through image processing algorithms. This substitution eliminates the need for physical loop installation while providing equivalent or superior triggering capability through digital means.
Solution Approach 2:
The system creates a digital copy of the vehicle detection function by capturing visual information through a camera and processing it algorithmically, rather than relying on the physical inductive loop's electromagnetic properties. This digital copying approach provides the same triggering function with lower infrastructure costs.
2Measurement precision
If high spatial resolution is used in video processing, then detection accuracy improves, but processing time increases
Solution Approach 1:
The patent segments the video processing task into multiple stages: first processing low-resolution frames for initial vehicle detection and triggering, then selectively processing only the identified regions of interest at high resolution. This segmentation allows the system to maintain detection accuracy for critical elements while reducing overall processing time by avoiding full-frame high-resolution analysis.
Solution Approach 2:
The system applies partial action by processing only the necessary portions of the video stream at high resolution - specifically, only the regions containing detected vehicles or potential license plates. The majority of the frame is processed at lower resolution, providing sufficient information for triggering while minimizing computational burden and processing time.
Data Source
AI summary
A method and system for real-time video triggering for traffic surveillance and photo enforcement comprises receiving a streaming video feed and performing a spatial uniformity correction on each frame of the streaming video feed and resampling the video feed to a lower spatial resolution. Motion blobs are then detected. Next a three-layered approach is used to identify candidate motion blobs which can be output to a triggering module to trigger a video collection action.