Camera Condition Monitoring and Readjustment by means of Noise and Blur

12/10/2021
by   Maik Wischow, et al.
5

Autonomous vehicles and robots require increasingly more robustness and reliability to meet the demands of modern tasks. These requirements specially apply to cameras because they are the predominant sensors to acquire information about the environment and support actions. A camera must maintain proper functionality and take automatic countermeasures if necessary. However, there is little work that examines the practical use of a general condition monitoring approach for cameras and designs countermeasures in the context of an envisaged high-level application. We propose a generic and interpretable self-health-maintenance framework for cameras based on data- and physically-grounded models. To this end, we determine two reliable, real-time capable estimators for typical image effects of a camera in poor condition (defocus blur, motion blur, different noise phenomena and most common combinations) by comparing traditional and retrained machine learning-based approaches in extensive experiments. Furthermore, we demonstrate how one can adjust the camera parameters (e.g., exposure time and ISO gain) to achieve optimal whole-system capability based on experimental (non-linear and non-monotonic) input-output performance curves, using object detection, motion blur and sensor noise as examples. Our framework not only provides a practical ready-to-use solution to evaluate and maintain the health of cameras, but can also serve as a basis for extensions to tackle more sophisticated problems that combine additional data sources (e.g., sensor or environment parameters) empirically in order to attain fully reliable and robust machines.

READ FULL TEXT

Authors

page 1

page 2

page 4

page 6

page 8

page 12

09/22/2021

A Method For Adding Motion-Blur on Arbitrary Objects By using Auto-Segmentation and Color Compensation Techniques

When dynamic objects are captured by a camera, motion blur inevitably oc...
12/08/2020

Digital Gimbal: End-to-end Deep Image Stabilization with Learnable Exposure Times

Mechanical image stabilization using actuated gimbals enables capturing ...
04/14/2022

Learning Spatially Varying Pixel Exposures for Motion Deblurring

Computationally removing the motion blur introduced by camera shake or o...
06/30/2022

HRFuser: A Multi-resolution Sensor Fusion Architecture for 2D Object Detection

Besides standard cameras, autonomous vehicles typically include multiple...
11/09/2021

Leveraging blur information for plenoptic camera calibration

This paper presents a novel calibration algorithm for plenoptic cameras,...
10/24/2019

Soft Prototyping Camera Designs for Car Detection Based on a Convolutional Neural Network

Imaging systems are increasingly used as input to convolutional neural n...
04/26/2020

Designing a physically-feasible colour filter to make a camera more colorimetric

Previously, a method has been developed to find the best colour filter f...

Code Repositories

Camera-Condition-Monitoring

Code basis for the paper "Camera Condition Monitoring and Readjustment by means of Noise and Blur" (2021)


view repo
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.