Hybrid Depth Sensing Pipeline for Tunable Accuracy
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Solution Overview
Problem
Current depth sensing techniques are used in isolation, lacking a standard pipeline that combines multiple methods to adjust and tune for real-time power, performance, resolution, and accuracy considerations, which limits their potential for enhanced accuracy and performance.
Innovation Solution
A hybrid depth sensing pipeline, known as Hybrid Tracking and Mapping (HTAM), is developed to combine various depth sensing techniques into a programmable pipeline, allowing for real-time adjustments and optimizations based on device capabilities, supporting stereoscopic, virtual stereoscopic, and multi-view stereoscopic reconstructions, and enabling variable resolution depth maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple depth sensing techniques are combined into a hybrid pipeline, then accuracy and performance are improved, but device complexity increases
Solution Approach 1:
The depth sensing pipeline is segmented into multiple independent technique modules (stereoscopic reconstruction, multi-view stereoscopic reconstruction, structured light scanning, time-of-flight measurement) that can be selectively activated. Each module processes depth data independently, allowing the system to combine results from multiple techniques without requiring complete integration of all components, thus improving accuracy while managing complexity.
Solution Approach 2:
The hybrid pipeline is designed with a universal processing framework that can handle multiple depth sensing techniques through a common architecture. The system uses a unified data structure and processing pipeline that accommodates different sensing methods, allowing the same infrastructure to support various techniques simultaneously, thereby reducing overall system complexity while maintaining multi-technique capability.
2Device complexity
If depth sensing techniques are used in isolation, then device complexity is reduced, but accuracy and performance are limited
Solution Approach 1:
The system merges multiple depth sensing techniques into a unified hybrid pipeline that processes and integrates depth data from different sources. By combining stereoscopic reconstruction, multi-view stereoscopic reconstruction, structured light scanning, and time-of-flight measurement in a single processing framework, the system achieves superior accuracy compared to isolated techniques while maintaining manageable complexity through shared processing infrastructure.
Solution Approach 2:
The depth sensing system uses a composite approach by integrating multiple sensing techniques with complementary strengths. Each technique contributes specific advantages (e.g., stereoscopic for wide area, structured light for precision, time-of-flight for speed), and their combined use creates a synergistic effect that achieves accuracy levels unattainable by any single technique alone.
3Use of energy by moving object
If real-time adjustments are enabled for power and performance optimization, then energy efficiency is improved, but system complexity increases
Solution Approach 1:
The hybrid pipeline implements dynamic configuration capabilities that allow real-time adjustment of active depth sensing techniques based on current power availability and performance requirements. The system can dynamically enable or disable specific modules (e.g., switching from power-intensive structured light scanning to less intensive stereoscopic reconstruction) without requiring complete system reconfiguration, thus optimizing power consumption while managing complexity through adaptive rather than static design.
Solution Approach 2:
The system changes operational parameters of the depth sensing pipeline in real-time, adjusting which techniques are active, their processing intensity, and data fusion strategies based on power conditions and performance needs. This parameter-based control allows flexible optimization of power consumption without requiring fundamental changes to the system architecture, maintaining relative simplicity while enabling adaptive energy efficiency.
Data Source
AI summary
An apparatus for a hybrid tracking and mapping is described herein. The apparatus includes logic to determine a plurality of depth sensing techniques. The apparatus also includes logic to vary the plurality of depth sensing techniques based on a camera configuration. Additionally, the apparatus includes logic to generate a hybrid tracking and mapping pipeline based on the depth sensing techniques and the camera configuration.