Video Timeline Generation for Object-Centric Surveillance Monitoring
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Solution Overview
Problem
Current security and surveillance camera systems face inefficiencies in identifying and monitoring video streams from multiple cameras, leading to missed or mislabeled events, as users must manually review streams from various angles, which is time-consuming and prone to errors.
Innovation Solution
A video processing system that identifies objects of interest in video streams, generates a timeline of these events, and allows users to playback relevant portions of the streams based on defined attributes, promoting streams with objects of interest for easier monitoring and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually monitor each video stream individually, then they can identify events of interest, but the process is time-consuming and prone to errors
Solution Approach 1:
The system enables self-service by having the video streams automatically analyze and flag events of interest without requiring continuous manual monitoring. The automated event detection system processes video data independently, generating alerts and timelines that users can review without time-consuming manual analysis of each stream.
Solution Approach 2:
The patent replaces the mechanical human monitoring process with an automated computer-based event detection system. The system uses image processing algorithms, object recognition, and temporal analysis to automatically identify events, substituting the manual mechanical process of watching and noting events with automated digital processing.
2Reliability
If users manually review video streams from multiple cameras, then they can identify events, but they may miss or mislabel events
Solution Approach 1:
The system implements feedback by continuously analyzing video streams and providing real-time alerts when events of interest are detected. The automated system sends notifications to users about detected events, allowing users to review only the relevant portions rather than continuously monitoring, thus improving both accuracy and ease of operation.
Solution Approach 2:
The system performs preliminary action by automatically pre-processing and analyzing video data to identify and filter events of interest before they are presented to users. The system proactively detects events, creates timelines, and prepares relevant video segments for review, eliminating the need for users to manually scan through entire streams.
3Adaptability or versatility
If the system processes multiple video streams simultaneously, then it can provide comprehensive coverage, but the complexity of managing and analyzing the streams increases
Solution Approach 1:
The system applies segmentation by dividing the complex task of managing multiple video streams into separate, independent processing modules. Each video stream is processed individually through dedicated analysis pipelines, and the results are then integrated into a unified timeline view. This modular approach maintains comprehensive coverage while reducing overall system complexity through organized modular architecture.
Data Source
AI summary
Systems, methods, and software to manage video streams for a timeline based on objects of interest identified in the video streams. In one example, a video processing system obtains video streams from video sources for a physical area and identifies one or more objects of interest in the physical area. The video processing system further identifies, for each of the video streams, one or more portions of the video stream that include at least one object of interest of the one or more objects of interest and generates a timeline to provide a visual display of the identified portions.