Video Segmentation via Pseudo Depth Maps from Uncalibrated Camera Arrays
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Solution Overview
Problem
Traditional chroma keying methods using green screens are cumbersome, expensive, and create unnatural acting environments, and they struggle with color spill and require manual effort, especially for outdoor and indoor sets.
Innovation Solution
A computer-implemented method for image segmentation using an uncalibrated camera array that computes pseudo depth maps from dense correspondences between camera images, allowing for virtual green screen placement and segmentation without geometric or photometric calibration, and refines edges using Markov random fields for accurate image segmentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional chroma keying using green screens is used, then video segmentation can be achieved, but setup costs and complexity increase significantly
Solution Approach 1:
The patent uses images captured by multiple cameras in an array to create a computational model that replicates the segmentation function of a physical green screen. Instead of requiring an actual green screen backdrop, the system captures images from multiple viewpoints and uses computational algorithms to identify and segment the foreground subject, effectively creating a virtual copy of the green screen functionality through software rather than physical props.
Solution Approach 2:
The patent replaces the mechanical/physical green screen system with a computational image processing system. Instead of using physical green screens, lighting equipment, and manual chroma keying techniques, the system uses multiple camera images, correspondence algorithms, and depth map computations to achieve automatic segmentation, substituting mechanical setup with automated computational methods.
2Reliability
If green screens are used for outdoor sets, then video segmentation is possible, but the effort and cost increase significantly
Solution Approach 1:
The system performs automatic segmentation without requiring manual setup of green screens or manual rotoscoping. The computational algorithm automatically processes the multi-camera images, computes correspondences, generates depth maps, and segments the foreground subject autonomously, making the system self-sufficient and eliminating the need for manual intervention in both setup and execution phases.
Solution Approach 2:
The patent creates a universal segmentation system that works for both indoor and outdoor scenes without requiring different setups. The multi-camera array and computational algorithm provide a flexible framework that can handle various lighting conditions, backgrounds, and scene types, making the system adaptable to different environments without the location-specific constraints of physical green screens.
3Reliability
If green screens are used indoors, then video segmentation can be achieved, but color spill onto foreground objects occurs
Solution Approach 1:
The patent introduces computational depth maps as an intermediary between the captured images and the final segmentation result. Instead of directly using color information from green screens (which causes color spill), the system computes pseudo-depth information from multi-camera correspondences and uses this intermediate depth data to guide the segmentation process, separating foreground and background based on depth rather than color, thereby eliminating color spill contamination.
Solution Approach 2:
The patent substitutes the optical/color-based chroma keying mechanism with a computational depth-based segmentation mechanism. Instead of relying on color separation techniques that are susceptible to color spill, the system uses geometric relationships from multi-camera views to compute depth information and perform segmentation, replacing the color-based mechanical process with a geometry-based computational process that is immune to color contamination.
4Ease of operation
If green screens are used, then video segmentation is simplified, but actors experience unnatural acting environments
Solution Approach 1:
The system creates a virtual segmentation environment that copies the functional benefits of green screens without the physical presence of green props. By using computational methods to achieve segmentation, the actual shooting environment can remain natural and unaltered, allowing actors to perform in realistic settings while the post-processing system creates the segmentation effect digitally.
Solution Approach 2:
Instead of modifying the physical environment with green screens to enable segmentation, the patent inverts the approach by keeping the environment natural and applying segmentation through computational processing of captured images. The segmentation is achieved not by changing the scene during filming but by processing the captured data afterward, reversing the traditional workflow and eliminating the need for artificial acting environments.
Data Source
AI summary
The disclosure provides an approach for image segmentation from an uncalibrated camera array. In one aspect, a segmentation application computes a pseudo depth map for each frame of a video sequence recorded with a camera array based on dense correspondences between cameras in the array. The segmentation application then fuses such pseudo depth maps computed for satellite cameras of the camera array to obtain a pseudo depth map at a central camera. Further, the segmentation application interpolates virtual green screen positions for an entire frame based on user input which provides control points and pseudo depth thresholds at the control points. The segmentation application then computes an initial segmentation based on a thresholding using the virtual green screen positions, and refines the initial segmentation by solving a binary labeling problem in a Markov random field to better align the segmentation with image edges and provide temporal coherency for the segmentation.