ISP Color Processing Using Z-Depth for 3D Video
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Solution Overview
Problem
Conventional 3D video systems lack effective methods to enhance color representation based on z-depth information, limiting their performance and cost-effectiveness.
Innovation Solution
A monoscopic video camera system utilizing an image sensor pipeline (ISP) captures 2D video and corresponding depth information, allowing for adaptive color processing based on z-depth data to enhance color representation and generate 3D images by configuring color-related parameters and hue adjustments for objects at varying depths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional 3D video systems are used, then basic 3D functionality is achieved, but color representation and performance are limited
Solution Approach 1:
The system performs preliminary depth estimation and object detection on captured 2D video frames before final 3D rendering. By pre-processing the video data to identify objects and their depth positions, the system can apply targeted color enhancements to specific depth planes, improving color accuracy without processing the entire scene uniformly, thus balancing performance and precision
Solution Approach 2:
The patent applies different color processing parameters to different depth planes and objects within the scene. Instead of uniform color enhancement across the entire image, the system selectively adjusts color properties (hue, saturation, brightness) for objects at specific depths, allowing optimized color representation for each depth layer while maintaining overall system efficiency
2Measurement precision
If multiple lenses are used to capture depth information, then 3D perception is improved, but system cost and complexity increase
Solution Approach 1:
The system introduces an computational intermediary layer that processes standard 2D video frames to extract depth information through object detection and depth estimation algorithms. This computational mediator enables 3D depth plane generation without requiring additional optical hardware, allowing the system to achieve depth accuracy through software processing of conventional camera input
Solution Approach 2:
The patent replaces the mechanical/optical approach of using multiple physical lenses with a computational approach using image processing algorithms. By substituting the mechanical depth-capture mechanism with software-based depth estimation from 2D frames, the system achieves similar 3D functionality while reducing hardware complexity and cost
3Ease of manufacture
If color processing is applied uniformly to all objects, then processing simplicity is maintained, but color accuracy for objects at different depths is reduced
Solution Approach 1:
The system segments the video scene into multiple depth planes and objects based on detected depth information. By dividing the scene into distinct depth layers, the system can apply separate color processing parameters to each segment, ensuring accurate color representation for objects at different depths while maintaining manageable processing complexity through systematic segmentation
Data Source
AI summary
A monoscopic video camera may capture, via at least one image sensor, two-dimensional video, and may capture, via at least one depth sensor, corresponding depth information for the captured two-dimensional video. The monoscopic video camera may then configure color related processing of video information corresponding to objects in the captured 2D video based on the captured corresponding depth information. Configuring color processing may comprise setting and/or adjusting color information associated with the objects. In this regard, setting and/or adjusting color information may be based on shadow, shade, and/or edge related information associated with the objects, which may be generated and/or modified based on the captured corresponding depth information based on the captured corresponding depth information. Configuring color processing may be based on surrounding regions adjacent to the objects. The surrounding regions adjacent to the objects may be determined based on the captured corresponding depth information.