Multi-Camera Video Playback With Event-Driven Segment Isolation
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Solution Overview
Problem
Existing video playback systems struggle with efficient browsing and searching of continuous video recordings, particularly when multiple cameras are involved, as they often require manual segmentation and lack intelligent filtering for events of interest.
Innovation Solution
A system that performs simultaneous playback of continuous video recordings from multiple cameras using intelligent grid selection, event-driven segmentation, and region-focused filtering, allowing for automatic generation of equal-length video segments based on user inputs and sensor data to highlight relevant events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual segmentation of video recordings is performed, then video playback can be organized into segments, but the time required for browsing and searching increases significantly
Solution Approach 1:
The system performs preliminary segmentation of video recordings into equal-length segments with generated metadata before playback. This pre-processing allows the playback system to directly access and display specific segments without manual navigation, significantly reducing browsing time while maintaining organized segment structure.
Solution Approach 2:
The system introduces metadata as an intermediary layer between the video content and the user interface. This metadata contains information about segment boundaries, timestamps, and content characteristics, enabling automated segment selection and display without requiring manual user intervention for navigation.
2Adaptability or versatility
If multiple cameras are monitored simultaneously, then comprehensive coverage is achieved, but the complexity of managing and reviewing video streams increases
Solution Approach 1:
The system segments video streams from multiple cameras into equal-length time-based segments and organizes them with metadata that includes camera identification and timestamps. This structured segmentation allows the system to manage multiple camera streams systematically, enabling users to review footage from any camera at any time without being overwhelmed by the complexity of multiple simultaneous streams.
3Measurement precision
If event-driven segmentation is implemented, then relevant events are highlighted, but the system complexity increases due to sensor data processing requirements
Solution Approach 1:
The system performs preliminary analysis of sensor data during the video segmentation process, generating metadata that flags segments containing detected events such as motion or audio anomalies. This pre-processing approach allows the system to identify and highlight relevant events without requiring complex real-time analysis during playback, reducing the perceived system complexity while maintaining high event detection accuracy.
Data Source
AI summary
Methods and systems, including computer programs encoded on a computer storage medium, are disclosed for simultaneous playback of continuous video recordings from multiple recording devices. A system obtains respective video data generated by multiple recording devices. Each video data includes multiple image frames. For each recording device: based on a time value, the system identifies events captured in the video data generated by the recording device. Based on an input variable corresponding to the events, the system: i) identifies an event stream that coincides with occurrence of a particular event captured in the video data; ii) determines a control value for segmenting image frames of the event stream; and iii) based on the control value, generates a video segment in response to isolating image frames of the event stream coinciding with the particular event. A graphical interface is generated that concurrently outputs each video segment for each recording device.