Composite Video Stream Object Recognition
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Solution Overview
Problem
In public-safety contexts, existing video-analysis techniques face challenges in quickly and accurately identifying objects of interest from large volumes of video data, especially when the object of interest is absent, due to time constraints and irrelevant video content.
Innovation Solution
The method involves detecting and tracking objects of interest in a composite video stream, generating a composite video stream that shows only the object's movements without background data, and storing it for searchable databases with metadata, allowing for efficient identification and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If object recognition is applied to analyze entire video streams, then identification accuracy is improved, but analysis time increases significantly
Solution Approach 1:
The patent extracts and isolates only the objects of interest from the composite video stream, separating them from the full video content. This extraction process creates a focused subset of video frames containing only relevant objects, enabling rapid analysis without sacrificing identification accuracy.
Solution Approach 2:
The patent segments the video analysis process into distinct phases: initial object detection in the composite stream, tracking of identified objects across frames, and generation of a segmented output stream containing only objects of interest. This segmentation allows the system to maintain high accuracy while reducing overall analysis time.
2Productivity
If fixed camera position tools are used for object extraction, then processing speed is improved, but adaptability to different scenarios deteriorates
Solution Approach 1:
The patent implements dynamic object tracking that adapts to moving objects and changing scene compositions. The system continuously updates object positions and characteristics across video frames, allowing it to handle diverse scenarios including moving cameras, changing lighting conditions, and varying object positions, while maintaining high processing speed.
Solution Approach 2:
The patent creates a universal object extraction system that can handle multiple video sources, different object types, and various camera configurations through a single integrated approach. The composite video stream processing methodology is applicable across diverse public safety scenarios, from surveillance to traffic monitoring.
Data Source
AI summary
Disclosed herein are methods and systems for object recognition and link integration in a composite video stream. One embodiment takes the form of a process that includes detecting an object of interest in a set of video frames. The process also includes tracking the movements of the detected object of interest across a subset of the video frames in the set of video frames. The process further includes generating a composite video stream from the video frames in the subset. The composite video stream shows the tracked movements of the detected object of interest without showing background data from the video frames in the subset. The process also includes outputting the generated composite video stream.