Depth Sensor Amplitude Segmentation for Near-Far Object Detection
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Solution Overview
Problem
Depth sensors using the time of flight (TOF) principle face challenges in accurately capturing depth information from scenes with objects at varying distances, as low signal levels from far objects result in poor signal-to-noise ratios, making it difficult to capture images from complex scenes with both near and far objects.
Innovation Solution
The method involves emitting source signals with different amplitudes towards a scene, capturing images based on the reflected signals, and using an image signal processor to generate a single image by interpolating images from signals with varying pixel values, allowing for improved depth information accuracy by distinguishing between near and far objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the depth sensor emits source signals to capture scenes with objects at varying distances, then the ability to detect both near and far objects is improved, but the signal-to-noise ratio deteriorates for far objects due to low signal levels
Solution Approach 1:
The patent segments the scene into different depth ranges (near objects and far objects) and uses different source signal amplitudes for each segment. By dividing the detection task into multiple parts based on distance, the system can optimize signal parameters for each segment, thereby improving the signal-to-noise ratio for far objects while maintaining the ability to detect both near and far objects.
Solution Approach 2:
The patent applies local quality by using different source signal amplitudes for different spatial regions. Specifically, higher amplitudes are used for far objects to improve signal strength, while lower amplitudes are used for near objects to avoid saturation. This localized optimization of signal parameters improves the overall measurement precision across the entire scene.
2Device complexity
If the depth sensor uses a single source signal amplitude, then the device complexity is reduced, but the accuracy of depth information deteriorates for scenes with multiple objects at different distances
Solution Approach 1:
The patent introduces dynamics by making the source signal amplitude variable rather than fixed. The light source driver dynamically adjusts the amplitude of source signals based on the depth information of detected objects. This dynamic adjustment enables the system to maintain high depth information accuracy for objects at different distances while managing complexity through controlled variability.
Solution Approach 2:
The patent applies parameter changes by varying the amplitude parameter of source signals according to the depth of detected objects. The light source driver modifies this parameter in real-time based on feedback from depth detection, allowing the system to optimize measurement precision for different spatial regions without requiring a completely complex device architecture.
3Adaptability or versatility
If the depth sensor captures images from scenes with both near and far objects, then the versatility of the system is improved, but the image quality deteriorates due to noise in low signal regions
Solution Approach 1:
The patent segments the image capture process into multiple passes, with each pass targeting specific depth ranges. By dividing the image capture into segments based on object distance, the system can apply optimized signal parameters to each segment, thereby improving overall image quality while maintaining the ability to capture diverse scenes with both near and far objects.
Solution Approach 2:
The patent applies preliminary action by performing depth detection and signal amplitude optimization before actual image capture. The system first detects depth information, then uses this information to pre-adjust source signal amplitudes for subsequent image capture operations. This preliminary optimization ensures high image quality for both near and far objects by preparing the signal parameters in advance.
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 the accuracy of depth information by effectively handling scenes with multiple objects at different distances, improving image quality by reducing noise and enhancing signal intensity through sequential emission of source signals with varying amplitudes.
Implementation Method 1
a depth sensor may measure a depth (or range. or distance) between the object and the sensor using a TOF measuring method. That is, the depth sensor may be used to measures a delay time between the transmission (or emission) of the source signal and return of the reflected portion of the source signal to the sensor
Implementation Method 2
The object may then reflect a portion of the source signal, and the reflected portion of the source signal is detected by a depth sensor
Data Source
AI summary
An image capture method performed by a depth sensor includes; emitting a first source signal having a first amplitude towards a scene, and thereafter emitting a second source signal having a second amplitude different from the first amplitude towards the scene, capturing a first image in response to the first source signal and capturing a second image in response to the second source signal, and interpolating the first and second images to generate a final image.