Depth Map Modification via Confidence-Based Segmentation
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Solution Overview
Problem
Existing depth map modification techniques are computationally intensive and inefficient, particularly when dealing with low-confidence depth values and depth holes, as they often require iterative smoothing and individual value checking.
Innovation Solution
The proposed solution involves dividing depth maps into sections based on confidence values, determining section confidences, and modifying the depth map by skipping smoothing and filling operations in high-confidence sections, thereby reducing computational intensity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If iterative smoothing and individual value checking are applied to the entire depth map, then depth accuracy is improved, but computational time and operations increase significantly
Solution Approach 1:
The depth map is divided into multiple depth sections based on confidence values. Each section is processed independently, allowing the system to apply smoothing operations selectively only to low-confidence sections while skipping high-confidence sections, thereby reducing overall computational time while maintaining depth accuracy where needed
Solution Approach 2:
Different processing strategies are applied to different regions of the depth map based on their confidence characteristics. Low-confidence sections receive iterative smoothing to improve accuracy, while high-confidence sections are skipped to save computational time, creating a locally optimized processing approach
2Reliability
If smoothing operations are applied to all depth values, then depth map quality is improved, but computational operations increase
Solution Approach 1:
Instead of applying smoothing operations to all depth values (excessive action), the system applies smoothing only to low-confidence depth sections where it is most needed (partial action). This reduces computational operations while maintaining sufficient depth map quality by focusing resources on problematic areas
3Measurement precision
If individual depth values are checked and modified, then depth precision is improved, but device complexity increases
Solution Approach 1:
The system segments the depth map into sections based on confidence values, reducing processing complexity by handling groups of values together rather than checking each individual value. This maintains depth precision through targeted processing while simplifying the overall processing architecture
Data Source
AI summary
Systems and techniques are described herein for modifying depth maps. For instance, a method for modifying depth maps is provided. The method may include obtaining a depth map comprising a plurality of depth values; obtaining a plurality of confidence values comprising a respective confidence value for each depth value of the plurality of depth values; dividing the depth map into a plurality of depth sections; determining, based on the plurality of confidence values, a plurality of section confidences comprising a respective section confidence for each of the plurality of depth sections; and modifying the depth map based on the plurality of section confidences.