Video Analytics Processor Pipeline Querying
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Solution Overview
Problem
Current methods for annotating images and videos based on objects present in them are labor-intensive and complicated, lacking efficient automated or guided processing solutions.
Innovation Solution
A method involving a processor that selects and applies processing pipelines to video streams to extract analytics data, synchronizes multiple video streams by identifying similarities, and uses a markup language to represent video inputs and actions, enabling efficient object identification and queryable data structures for user interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual annotation methods are used, then annotation accuracy can be maintained, but labor intensity increases significantly
Solution Approach 1:
The system enables automated annotation by having the computer vision system process video streams and generate annotations independently without requiring manual intervention for each annotation task, thus resolving the contradiction between accuracy and labor intensity
Solution Approach 2:
The patent replaces manual mechanical annotation processes with automated computer vision algorithms that detect and annotate objects in video streams, substituting human labor with computational mechanisms to maintain accuracy while reducing labor intensity
2Measurement precision
If multiple processing pipelines are applied to video streams, then object identification completeness improves, but processing complexity increases
Solution Approach 1:
The system divides the complex annotation task into separate processing pipelines, each handling specific object types or annotation tasks independently, then combines results. This segmentation allows complete object identification while managing complexity through modular architecture
Solution Approach 2:
The processing pipelines are designed as reusable, multi-functional modules that can be selectively applied to different video streams and object types, allowing the system to handle diverse annotation requirements through a unified framework that reduces overall complexity
3Measurement precision
If video streams are synchronized to correlate information, then location and time accuracy improve, but computational requirements increase
Solution Approach 1:
The system performs preliminary synchronization of video streams before detailed correlation analysis, establishing time and location references in advance. This preliminary action enables accurate correlation while reducing the computational burden during subsequent analysis by pre-organizing data structures
Solution Approach 2:
The patent introduces intermediate data structures and correlation engines that act as mediators between video streams, facilitating efficient synchronization and correlation. These intermediaries organize and compare data from multiple streams, achieving accurate location and time correlation while managing computational requirements through optimized data handling
Data Source
AI summary
In a method of processing video images, a processor might obtain a video stream, select a set of processing pipelines from a plurality of processing pipelines, apply the set of processing pipelines to the video stream to obtain a data set of analytics data, wherein the pipeline analytics data for a processing pipeline of the set of processing pipelines comprises data about images of the video images, store the pipeline analytics data of each processing pipeline into a queryable data structure, receive queries from a user interface, and return portions of the video stream, or references thereto, in response to the queries.