Depth-Map Anchoring for Real-Time Computational Photography Focus
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Solution Overview
Problem
Existing computational photography techniques in mobile devices struggle with maintaining focus on objects as the user changes perspective, requiring object recognition algorithms that consume processing resources and specialized sensors, and fail to effectively manage depth-based image enhancements.
Innovation Solution
Implementing depth maps and anchors in computational photography to track and maintain focus on a depth of interest, allowing for real-time image editing based on depth information, enabling pixel enhancement and distortion at specific depths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If object recognition algorithms are used to maintain focus on objects, then focus accuracy is improved, but processing resource consumption increases
Solution Approach 1:
The image is divided into multiple depth layers using depth map information. Instead of processing the entire image uniformly, the system segments pixels into different depth groups (foreground, midground, background) and applies selective enhancement only to the anchored depth layer, reducing overall processing resources while maintaining focus accuracy.
Solution Approach 2:
The patent applies different processing qualities to different regions of the image based on depth. The anchored depth layer receives full-resolution enhancement and sharp focus, while other depth layers receive reduced processing or blur effects. This local quality differentiation maintains focus accuracy on the subject while reducing processing resources for the entire image.
2Measurement precision
If specialized sensors are used for depth detection, then depth measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces depth maps as an intermediary data structure that can be generated from existing camera sensors without requiring specialized depth-sensing hardware. The depth map serves as a mediator between standard image capture and depth-based processing, enabling depth-aware operations while avoiding the need for complex specialized sensors.
Solution Approach 2:
Instead of using specialized sensors to directly capture depth information, the system creates a depth map as a computational copy or representation of depth data derived from standard image processing techniques. This copying approach allows depth measurement without adding specialized sensing hardware to the device.
3Manufacturing precision
If full image processing is applied to all pixels, then image quality is improved, but processing time increases
Solution Approach 1:
The patent applies the principle of partial action by processing only the necessary portion of the image at full quality. Pixels at the anchored depth receive complete enhancement processing, while pixels at other depths receive reduced or no processing. This partial processing approach maintains image quality for the focal subject while dramatically reducing overall processing time.
Solution Approach 2:
The image processing is segmented into depth-based groups, allowing the system to apply different processing levels to different segments. The foreground/anchored depth segment receives full processing for high quality, while background segments receive minimal processing, optimizing the balance between image quality and processing time.
4Productivity
If depth-based selective processing is implemented, then processing efficiency is improved, but algorithm complexity increases
Solution Approach 1:
The patent performs preliminary action by pre-computing and storing depth map information for the entire image before applying selective processing. This preliminary depth analysis creates a ready-to-use depth classification that simplifies subsequent processing steps, allowing the system to efficiently select which pixels to enhance without complex real-time decisions during the actual image processing phase.
Data Source
AI summary
A method including receiving an image as a portion of a real-world space, placing an anchor on the image, determining a position of the anchor, determine a depth associated with the position of the anchor, applying an image editing algorithm based on the depth to the captured image, and rendering the edited image.