Automated Object Identification in Paused Video Frames
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Solution Overview
Problem
Current manual methods for annotating objects in video images are labor-intensive and lack accuracy, especially when dealing with large numbers of objects or video files, leading to inefficiencies and inconsistencies in video advertising.
Innovation Solution
A method and apparatus for automatically identifying objects in paused video images by receiving information from a client, extracting static images, using image segmentation and feature extraction techniques to determine object areas and features, and matching them with a pre-generated library to provide accurate object information for display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual dotting method is used to annotate objects in video images, then object information can be displayed in video playing process, but excessive manual labor is required and processing speed is slow
Solution Approach 1:
The patent replaces the manual mechanical dotting process with an automated computer vision system. The system uses image recognition algorithms to automatically identify objects in video frames, extract their features, and annotate them without human intervention. This substitution of manual mechanical operation with an automated computational system directly resolves the contradiction by eliminating excessive manual labor while maintaining high processing speed.
Solution Approach 2:
The system enables self-service by allowing the video processing system to automatically perform object identification and annotation without requiring manual intervention. The automated pipeline processes video frames, identifies objects, and generates annotations independently, thereby eliminating the need for manual dotting labor while maintaining efficient processing speed.
2Measurement precision
If manual dotting method is used to annotate objects in video images, then object information can be displayed, but identification accuracy cannot be controlled and inconsistency occurs
Solution Approach 1:
The patent transforms the subjective manual identification process into an objective automated process by changing the parameters from human experience-based judgment to algorithmic feature extraction and matching. The system uses consistent computational parameters (feature extraction algorithms, similarity thresholds) to identify objects, ensuring uniform accuracy across all video files without dependency on individual annotators' experience or knowledge.
Solution Approach 2:
The patent replaces the manual mechanical dotting process with an automated computer vision system. The system uses image recognition algorithms to automatically identify objects in video frames, extract their features, and annotate them without human intervention. This substitution of manual mechanical operation with an automated computational system directly resolves the contradiction by eliminating excessive manual labor while maintaining high processing speed.
3Quantity of substance
If large number of objects exist in video files, then comprehensive advertising coverage is achieved, but manual processing becomes impossible to complete efficiently
Solution Approach 1:
The patent applies segmentation by dividing the video processing task into discrete frames and further segmenting each frame into regions of interest. The system processes video files frame-by-frame and identifies objects within each frame independently, allowing parallel processing and efficient handling of large quantities of objects across multiple video files without compromising processing efficiency.
Solution Approach 2:
The patent replaces the manual mechanical dotting process with an automated computer vision system. The system uses image recognition algorithms to automatically identify objects in video frames, extract their features, and annotate them without human intervention. This substitution of manual mechanical operation with an automated computational system directly resolves the contradiction by eliminating excessive manual labor while maintaining high processing speed.
Data Source
AI summary
The disclosure discloses a method and apparatus for identifying objects in paused video images, a method and apparatus for displaying object information on paused video images, and a system for displaying object information on paused video images. The method of identifying objects in paused video images comprises: receiving, from a client, information associated with the paused video images; obtaining, based on the received information associated with the paused video images, the at least one static image corresponding to a paused video of the client; identifying the objects from the at least one static image and obtaining object information; and sending, to the client, identified position information and the object information associated with the objects in the at least one static image. With the solutions provided in the disclosure and by combining client ends and servers, the disclosure achieves the functions of automatically identifying object in paused video images and displaying object information, thereby effectively improving the efficiency and accuracy of advertising in a video play process.