Event-Based Vision Sensor Adaptive Depth Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Depth sensors and conventional image sensors in computing devices consume high levels of power and generate significant data, making them expensive to operate in terms of power and memory usage.
Innovation Solution
The integration of event-based vision sensors, which intrinsically compress data and operate with low power consumption, allows for continuous monitoring of environmental changes with high temporal resolution, enabling adaptive control schemes for depth sensing and camera operations to optimize power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If depth sensors are operated continuously to maintain accurate environmental models, then measurement precision is improved, but power consumption increases
Solution Approach 1:
The system implements periodic depth sensing operations triggered by motion detection events rather than continuous operation. The event-based vision sensor detects motion events, and depth sensing is activated periodically only when motion is detected, reducing power consumption while maintaining measurement precision when needed
Solution Approach 2:
The system uses feedback from the event-based vision sensor to dynamically control depth sensing operations. Motion detection feedback triggers depth measurements only when environmental changes occur, creating a closed-loop control system that optimizes power consumption based on actual sensing needs
2Measurement precision
If conventional image sensors operate at high frequencies and resolutions to capture environmental changes, then measurement precision is improved, but power consumption and data volume increase
Solution Approach 1:
The system extracts only the essential motion information from the visual scene using event-based sensors, rather than capturing complete high-resolution images. Only pixels that detect motion generate events, extracting minimal necessary data while maintaining detection precision
Solution Approach 2:
The system changes the operational parameters of the sensing system by using event-based sensors that operate at high temporal resolution without the fixed frame rate constraints of conventional cameras. This allows adaptive sampling that maintains precision while reducing power consumption
3Measurement precision
If conventional image sensors operate at high resolutions to capture detailed environmental information, then measurement precision is improved, but memory usage and data processing requirements increase
Solution Approach 1:
The system extracts only motion-related information from the visual scene, generating sparse event data instead of complete high-resolution images. This extraction approach maintains precision for detecting environmental changes while dramatically reducing data volume
Solution Approach 2:
The system uses periodic event-based sampling that captures environmental changes only when motion occurs, rather than continuously capturing full-resolution images. This reduces data volume while maintaining accuracy for dynamic scene monitoring
Data Source
AI summary
A method and system comprising one or more event-based vision sensors for monitoring an environment and one or more depth sensors monitoring the environment as well as potentially additional sensors to monitor the environment such as inertial measurement units and image sensors. The device as a processor assembly will then monitor the event-based vision sensor and the depth sensor and other sensors and determine whether to adapt a control scheme, such as activate, the depth sensor to acquire depth information of the environment based on the response of the event-based vision sensor. This approach leverages advantages of event-based sensors to reduce the power consumption but still react quickly to such changes by continuously measuring intervals directly relating to the minimally admitted delays in the application for which depth measurements or inferred data are used.