Multimedia Blending via Depth Layer Segmentation
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Solution Overview
Problem
Existing methods for blending multimedia content, such as images and videos, lack efficiency in combining multiple sources with depth information to create seamless and contextually accurate blended content, often requiring manual selection and lacking automation in layering and depth management.
Innovation Solution
A method and apparatus that facilitate access to multiple multimedia sources with depth information, generate a blend map by defining depth layers with specific limits, and blend content based on these layers, allowing for automated selection and combination of pixels to create a seamless blended output.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual selection and layering methods are used for blending multimedia content, then flexibility in content selection is improved, but productivity and automation are worsened
Solution Approach 1:
The system performs automatic depth-based layering and blending without requiring manual user intervention. The processor automatically analyzes depth information from multiple images, generates depth layers, and blends them according to predefined rules, making the system self-sufficient and eliminating the need for manual operation while maintaining high-quality results
Solution Approach 2:
The invention changes the parameter of automation by introducing automatic depth-based segmentation and layering algorithms. By transforming manual selection processes into automated parameter-driven operations (using depth information, distance metrics, and blending weights), the system achieves both high productivity and operational flexibility simultaneously
2Device complexity
If predefined blend maps are used for blending, then device complexity is reduced, but manufacturing precision and contextuality of blending are worsened
Solution Approach 1:
The system segments the blending process into distinct depth-based layers automatically. By dividing the image content into foreground, middle-ground, and background layers based on depth information, the system achieves precise contextual blending without requiring complex manual blend map definitions, thus maintaining simplicity while improving accuracy
Solution Approach 2:
The invention introduces depth information as an additional dimension for controlling the blending process. Instead of relying solely on 2D spatial coordinates in predefined blend maps, the system uses 3D depth data to automatically determine layer assignments and blending parameters, thereby simplifying the user interface while significantly improving blending precision and contextuality
3Productivity
If automated depth-based layering is implemented, then productivity is improved, but device complexity increases
Solution Approach 1:
The system introduces depth information as an intermediary element that mediates between the input images and the blending output. By using depth maps and depth-based distance calculations as intermediate representations, the system automates the complex task of layer identification and assignment without requiring direct complex logic in the blending engine itself
Solution Approach 2:
The invention performs preliminary depth analysis and layer generation before the actual blending operation. By pre-processing the input images to extract depth information, generate depth layers, and assign contents to appropriate layers in advance, the system simplifies the subsequent blending process while maintaining high automation and productivity
Data Source
AI summary
In an example embodiment a method, apparatus and computer program product are provided. The method includes facilitating access to a plurality of source multimedia content, wherein at least one source multimedia of the plurality of source multimedia content comprises corresponding depth information. The method further includes generating a blend map by defining a plurality of depth layers. At least one depth layer of the plurality of depth layers is associated with a respective depth limit. Defining the at least one depth layer comprises selecting pixels of the at least one depth layer from the at least one source multimedia content of the plurality of source multimedia content based on the respective depth limit associated with the at least one depth layer and the corresponding depth information of the at least one source multimedia content. The method also includes blending the plurality of source multimedia content based on the blend map.