Video Object Recognition via Frame Buffering
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Solution Overview
Problem
Existing systems fail to effectively identify and provide information about objects within images or videos from sources other than a device's camera, such as television broadcasts or pre-recorded videos, limiting user interaction and engagement with the content.
Innovation Solution
A system that buffers video frames from various sources, performs image processing, and uses object recognition algorithms to identify objects, allowing users to navigate and take actions on recognized items through a user interface, even when the device's camera is not directly capturing the content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If object recognition is performed on video frames from external sources (television broadcasts, pre-recorded videos), then user interaction and engagement with content is enhanced, but the system complexity increases due to buffering, image processing, and integration with diverse video sources
Solution Approach 1:
The system is designed to handle multiple video sources (camera, television broadcast, pre-recorded videos) through a unified object recognition pipeline. The same buffering and image processing mechanisms work across all input sources, allowing one system to serve multiple functions and content sources without requiring separate specialized systems for each source type.
Solution Approach 2:
The system introduces intermediary components (buffering mechanism, image processing module) that act as mediators between the diverse video sources and the object recognition algorithms. These intermediaries standardize the input format and prepare the data uniformly, simplifying the overall system architecture by abstracting the complexity of handling different source formats.
2Loss of time
If real-time object recognition is performed on buffered video frames, then supplemental content can be provided immediately, but processing time and computational resources are consumed
Solution Approach 1:
The system performs preliminary buffering of video frames and pre-processing of images before object recognition is needed. By maintaining a buffer of recent frames and pre-processing them, the system can quickly identify objects without waiting for real-time processing of each new frame, reducing response time while distributing the computational load over time rather than concentrating it at the moment of recognition.
3Ease of operation
If the system processes and identifies objects in video content, then user engagement is enhanced, but the device complexity increases due to integration with diverse video sources and real-time processing requirements
Solution Approach 1:
The system automatically buffers video frames, processes images, and identifies objects without requiring manual intervention or complex user configuration. The object recognition system operates autonomously on the buffered content, providing supplemental information and enhancing engagement while hiding the underlying system complexity from the user. The interface presents simplified interaction capabilities while the background processes handle the complex integration and processing.
Data Source
AI summary
A system for performing object recognition on images in an image series, for example from a broadcast television signal or video-on-demand source. The system buffers images from the image series and accesses the buffer when an indication is received to start object recognition. The buffered images are sent to a recognition server, which returns object data for objects found in the image. The objects are then navigable using a user interface, through which the user can obtain additional information about the objects, or perform additional functions, such as adding the object to a shopping cart, etc.