Sparse Depth Sensing Using Digital Pixel Sensor
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Structured light-based depth sensing in artificial reality systems faces limitations due to ambient light interference, which reduces signal-to-noise ratio and increases computational complexity, making it challenging to achieve accurate and reliable depth sensing in high ambient light environments with low computational load.
Innovation Solution
A depth sensing system that generates a sparse grid array of light pulses sequentially and uses a sensor array to sense these pulses, calculating depth information based on both positional and temporal information of the pulses, while locking pixels to preserve projection time information and comparing sensed light pulses to ambient illumination values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If structured light patterns are projected continuously to enable depth sensing, then measurement precision is improved, but device complexity and computational load increase
Solution Approach 1:
The system projects light patterns periodically rather than continuously, using temporal modulation to encode depth information. The projector alternates between projecting structured light patterns and non-projecting states, creating a time-varying signal that enables depth measurement through temporal correlation analysis, thereby reducing computational complexity while maintaining measurement precision
Solution Approach 2:
The system pre-calculates and stores projected light pattern information before actual depth measurement occurs. By preparing the structured light patterns in advance and using them as reference for comparison during measurement, the system reduces real-time computational requirements while maintaining accurate depth sensing
2Reliability
If structured light patterns are projected in bright ambient light conditions, then depth sensing capability is maintained, but signal-to-noise ratio decreases
Solution Approach 1:
The system incorporates feedback mechanisms where the captured images are processed to identify projected pattern correspondences, and this information feeds back to adjust subsequent projection timing and pattern selection. This feedback loop enables the system to adapt to ambient light conditions dynamically, maintaining signal-to-noise ratio by selecting optimal projection moments when ambient light interference is minimized
Solution Approach 2:
By projecting light patterns periodically rather than continuously, the system creates temporal separation between projection and capture events. This periodic operation allows the system to synchronize projections with lower ambient light interference periods, improving signal-to-noise ratio while maintaining depth sensing reliability through temporal correlation
3Device complexity
If light pulse projection is made sequential to reduce computational load, then device complexity is reduced, but measurement precision may be compromised
Solution Approach 1:
The system adds the temporal dimension to depth measurement by sequentially projecting light patterns at different time points and capturing their reflections. This temporal dimension provides additional information that compensates for the reduced spatial sampling, enabling accurate depth measurement through time-of-flight calculation while maintaining low computational load through simple temporal correlation analysis
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances depth sensing accuracy and reduces computational complexity by leveraging temporal and spatial information of light pulses, improving performance in high ambient light conditions.
Implementation Method 1
A projector sequentially generates light pulses to form a sparse grid array. The light pulses reflect off objects in an environment and are reflected towards a sensor array.
Implementation Method 2
The sensor array sequentially senses the reflected light pulses across pixels of the sensor array. A depth sensing system calculates depth information of objects in the environment based on the sequential nature of the pulse generation and the pulse sensing.
Data Source
AI summary
A projector sequentially generates light pulses to form a sparse grid array. The light pulses reflect off objects in an environment and are reflected towards a sensor array. The sensor array sequentially senses the reflected light pulses across pixels of the sensor array. A depth sensing system calculates depth information of objects in the environment based on the sequential nature of the pulse generation and the pulse sensing. The depth sensing system calculates depth information based on both the positional and temporal information of generated light pulses, and the positional and temporal information of sensed light pulses. The depth sensing system may generate a representation of the environment based on the depth information.