Performance Evaluation and Integration of Distortion Mitigation Methods for Fisheye Video Object Detection

The distortion observed in fisheye cameras has proven to be a persistent challenge for numerous state-of-the-art object detection algorithms, instigating the development of various techniques aimed at mitigating this issue. This study aims to evaluate various methods for mitigating distortion in fis...

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Main Authors: Du, John Benedict, Mayuga, Gian Paolo, Guico, Maria Leonora
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Published: Archīum Ateneo 2024
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Online Access:https://archium.ateneo.edu/ecce-faculty-pubs/161
https://archium.ateneo.edu/context/ecce-faculty-pubs/article/1155/viewcontent/21211_41688_1_PB.pdf
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Institution: Ateneo De Manila University
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spelling ph-ateneo-arc.ecce-faculty-pubs-11552024-09-23T03:16:25Z Performance Evaluation and Integration of Distortion Mitigation Methods for Fisheye Video Object Detection Du, John Benedict Mayuga, Gian Paolo Guico, Maria Leonora The distortion observed in fisheye cameras has proven to be a persistent challenge for numerous state-of-the-art object detection algorithms, instigating the development of various techniques aimed at mitigating this issue. This study aims to evaluate various methods for mitigating distortion in fisheye camera footage and their impact on video object detection accuracy and speed. Using Python, OpenCV, and third-party libraries, the researchers modified and optimized said methods for video input and created a framework for running and testing different distortion correction methods and object detection algorithm configurations. Through experimentation with different datasets, the study found that undistorting the image using the longitude-latitude correction with the YOLOv3 object detector provided the best results in terms of accuracy (PASCAL: 68.9%, VOC-360: 75.1%, WEPDTOF: 15.9%) and speed (38 FPS across all test sets) for fisheye footage. After measuring the results to determine the best configuration for video object detection, the researchers also developed a desktop application that incorporates these methods and provides real-time object detection and tracking functions. The study provides a foundation for improving the accuracy and speed of fisheye camera setups, and its findings can be valuable for researchers and practitioners working in this field. 2024-09-01T07:00:00Z text application/pdf https://archium.ateneo.edu/ecce-faculty-pubs/161 https://archium.ateneo.edu/context/ecce-faculty-pubs/article/1155/viewcontent/21211_41688_1_PB.pdf Electronics, Computer, and Communications Engineering Faculty Publications Archīum Ateneo Distortion mitigation Fisheye cameras Image remapping Longitudinal-latitude correction Real-time tracking Video object detection YOLOv3 Computer Engineering Electrical and Computer Engineering Electrical and Electronics Engineering
institution Ateneo De Manila University
building Ateneo De Manila University Library
continent Asia
country Philippines
Philippines
content_provider Ateneo De Manila University Library
collection archium.Ateneo Institutional Repository
topic Distortion mitigation
Fisheye cameras
Image remapping
Longitudinal-latitude correction
Real-time tracking
Video object detection
YOLOv3
Computer Engineering
Electrical and Computer Engineering
Electrical and Electronics
Engineering
spellingShingle Distortion mitigation
Fisheye cameras
Image remapping
Longitudinal-latitude correction
Real-time tracking
Video object detection
YOLOv3
Computer Engineering
Electrical and Computer Engineering
Electrical and Electronics
Engineering
Du, John Benedict
Mayuga, Gian Paolo
Guico, Maria Leonora
Performance Evaluation and Integration of Distortion Mitigation Methods for Fisheye Video Object Detection
description The distortion observed in fisheye cameras has proven to be a persistent challenge for numerous state-of-the-art object detection algorithms, instigating the development of various techniques aimed at mitigating this issue. This study aims to evaluate various methods for mitigating distortion in fisheye camera footage and their impact on video object detection accuracy and speed. Using Python, OpenCV, and third-party libraries, the researchers modified and optimized said methods for video input and created a framework for running and testing different distortion correction methods and object detection algorithm configurations. Through experimentation with different datasets, the study found that undistorting the image using the longitude-latitude correction with the YOLOv3 object detector provided the best results in terms of accuracy (PASCAL: 68.9%, VOC-360: 75.1%, WEPDTOF: 15.9%) and speed (38 FPS across all test sets) for fisheye footage. After measuring the results to determine the best configuration for video object detection, the researchers also developed a desktop application that incorporates these methods and provides real-time object detection and tracking functions. The study provides a foundation for improving the accuracy and speed of fisheye camera setups, and its findings can be valuable for researchers and practitioners working in this field.
format text
author Du, John Benedict
Mayuga, Gian Paolo
Guico, Maria Leonora
author_facet Du, John Benedict
Mayuga, Gian Paolo
Guico, Maria Leonora
author_sort Du, John Benedict
title Performance Evaluation and Integration of Distortion Mitigation Methods for Fisheye Video Object Detection
title_short Performance Evaluation and Integration of Distortion Mitigation Methods for Fisheye Video Object Detection
title_full Performance Evaluation and Integration of Distortion Mitigation Methods for Fisheye Video Object Detection
title_fullStr Performance Evaluation and Integration of Distortion Mitigation Methods for Fisheye Video Object Detection
title_full_unstemmed Performance Evaluation and Integration of Distortion Mitigation Methods for Fisheye Video Object Detection
title_sort performance evaluation and integration of distortion mitigation methods for fisheye video object detection
publisher Archīum Ateneo
publishDate 2024
url https://archium.ateneo.edu/ecce-faculty-pubs/161
https://archium.ateneo.edu/context/ecce-faculty-pubs/article/1155/viewcontent/21211_41688_1_PB.pdf
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