Event-Driven Vision Sensor Thresholds for Distinct Signal Processing
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Solution Overview
Problem
Existing event-driven vision sensors lack the capability to differentiate processing based on the intensity of light changes, limiting their application in scenarios requiring distinct handling of events with varying light intensities.
Innovation Solution
An event-driven vision sensor system with a sensor array comprising sensors that generate different event signals based on predefined thresholds, allowing for distinct processing units to handle events with varying light intensities, including first and second sensors for different light intensity changes, and additional sensors in subsequent embodiments for more nuanced detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single threshold is used for event detection, then the device complexity is low, but the ability to differentiate processing based on light intensity changes is lost
Solution Approach 1:
The sensor array is segmented into multiple types of sensors (first sensors with first threshold, second sensors with second threshold) that detect different light intensity changes. This segmentation enables the system to differentiate between various event types based on their light intensity characteristics, resolving the contradiction between adaptability and device complexity.
Solution Approach 2:
Different sensors within the array are assigned different threshold values and detection characteristics based on their local function. First sensors are optimized for detecting smaller light intensity changes while second sensors detect larger changes, allowing each sensor type to specialize in specific event detection scenarios, thereby achieving differentiated processing capability.
2Measurement precision
If multiple sensor types with different thresholds are used, then event differentiation capability is improved, but the processing complexity increases
Solution Approach 1:
The processing system is segmented into multiple processing units, each dedicated to handling events from specific sensor types. First processing units handle events from first sensors while second processing units handle events from second sensors, reducing the complexity each unit must manage while maintaining overall detection precision.
Solution Approach 2:
Event signals serve as intermediaries that carry information about which sensor type detected the event and its characteristics. This intermediary mechanism allows the system to route different event types to appropriate processing units without requiring complex centralized decision-making, thus managing processing complexity effectively.
3Reliability
If all pixels are scanned in every predetermined period, then no events are missed, but the operating speed and power efficiency are reduced
Solution Approach 1:
Instead of continuous scanning, the system uses periodic event-triggered detection where sensors only generate signals when light intensity changes exceed their thresholds. This periodic action based on actual events maintains reliability by ensuring no significant events are missed while dramatically improving operating speed and reducing power consumption compared to continuous scanning.
Solution Approach 2:
The event-driven vision sensor enables pixels to autonomously detect and signal when they detect light intensity changes, eliminating the need for centralized control and continuous scanning. Each pixel serves itself by monitoring its own environment and generating events independently, which maintains detection reliability while improving speed and efficiency.
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
Enables separate processing of events with different light intensities, enhancing detection and localization accuracy by distinguishing between high and low confidence events, and supporting multiple event types with maintained speed and reduced latency.
Implementation Method 1
an event-driven vision sensor in which a pixel detects a change in intensity of incident light to time-asynchronously generate a signal
Data Source
AI summary
Provided is a system including an event-driven vision sensor including a sensor array in which a first sensor and a second sensor are arrayed in a predetermined pattern, the first sensor being configured to generate a first event signal when detecting a change in intensity of light larger than a first threshold, the second sensor being configured to generate a second event signal when detecting a change in intensity of light larger than a second threshold larger than the first threshold, and an information processing device including a first processing unit configured to execute first processing when the first event signal is received and the second event signal is not received, and a second processing unit configured to execute second processing different from the first processing when the second event signal is received.