Video Object Isolation via Segmentation and Extraction
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Solution Overview
Problem
Viewers are unable to focus on specific objects of interest within video streams without having to watch the entire video, as existing systems lack the capability to isolate and present only the relevant content.
Innovation Solution
A method that identifies and isolates frames containing an object of interest within a video stream using audio and video features, segmenting the stream into chunks, and generating a target video stream that includes only the object of interest, allowing viewers to focus on specific individuals or objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If viewers watch the entire video stream to find specific objects of interest, then they can ensure complete coverage of all content, but they waste time watching irrelevant content and objects
Solution Approach 1:
The system segments the video stream into individual frames and identifies objects within each frame using image recognition technology. This allows the system to separate and isolate specific objects of interest from the overall video content, enabling viewers to watch only relevant segments rather than the entire video stream.
Solution Approach 2:
The system extracts and isolates frames containing objects of interest from the complete video stream. By using image recognition to identify specific objects and then extracting only those frames, the system removes irrelevant content while preserving all instances of the desired objects, resolving the contradiction between time efficiency and content completeness.
2Measurement precision
If the system processes every frame to identify objects of interest, then it can ensure accurate detection, but it increases processing complexity and computational requirements
Solution Approach 1:
The system performs preliminary processing by pre-processing video frames to prepare them for object detection. This includes operations such as normalization, feature extraction, and preliminary filtering that simplify subsequent detection tasks, thereby maintaining detection accuracy while reducing the complexity of the main processing stage.
Solution Approach 2:
The system dynamically adjusts processing based on detected objects. Once an object of interest is identified in a frame, the system can adjust processing intensity for subsequent frames, maintaining high detection accuracy for critical moments while reducing processing complexity during less significant segments of the video.
Data Source
AI summary
Embodiments are related to processing of a source video stream for generation of a target video stream that includes an object of interest to a viewer. In some embodiments, the target video stream may exclusively or primarily include the performance of the object of interest to the viewer, without including other persons in that video. This allows a viewer to focus on an object of his or her interest and not necessarily have to view the performances of other objects in the source video stream.