Ahmed Abdelsalam , Mostafa Mansour , Jari Porras , Ari Happonen
{"title":"ZED 2i 立体摄像机在室内环境中的深度精度分析","authors":"Ahmed Abdelsalam , Mostafa Mansour , Jari Porras , Ari Happonen","doi":"10.1016/j.robot.2024.104753","DOIUrl":null,"url":null,"abstract":"<div><p>Accurate depth information is crucial for autonomous systems to navigate and interact safely with their surroundings. Passive stereo-vision cameras, such as the ZED 2i, obtain depth information through stereo-image analysis and triangulation. The study measures and assesses the true capabilities of the ZED 2i camera in a real indoor office environment. Furthermore, the study provides a standard test setup to reproduce similar benchmarks with different depth cameras. To achieve the set goals, an experiment was devised and carried out in an office environment to determine the camera depth error and Root Mean Square Error (RMSE) of the depth estimates at different distances using four different image resolutions. The results reveal that the depth error has heavy tails, implying that outliers substantially impact accuracy. Hence, depth errors should not be modeled as normally distributed errors. Moreover, only two out of four resolutions provided the capability of acquiring depth data up to 18 m. These insights provide guidelines for understanding the ZED 2i camera's true capabilities, determining its suitability for different applications and environments, and giving baselines for future tests of other competing sensor units. Furthermore, the study offers a simple, inexpensive, and laboratory space-free, yet effective setup that does not need extensive equipment or complex configurations to facilitate the benchmarking of depth cameras in different working environments.</p></div>","PeriodicalId":49592,"journal":{"name":"Robotics and Autonomous Systems","volume":"179 ","pages":"Article 104753"},"PeriodicalIF":4.3000,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0921889024001374/pdfft?md5=78c013418bab605b62edc7c64d077911&pid=1-s2.0-S0921889024001374-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Depth accuracy analysis of the ZED 2i Stereo Camera in an indoor Environment\",\"authors\":\"Ahmed Abdelsalam , Mostafa Mansour , Jari Porras , Ari Happonen\",\"doi\":\"10.1016/j.robot.2024.104753\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Accurate depth information is crucial for autonomous systems to navigate and interact safely with their surroundings. Passive stereo-vision cameras, such as the ZED 2i, obtain depth information through stereo-image analysis and triangulation. The study measures and assesses the true capabilities of the ZED 2i camera in a real indoor office environment. Furthermore, the study provides a standard test setup to reproduce similar benchmarks with different depth cameras. To achieve the set goals, an experiment was devised and carried out in an office environment to determine the camera depth error and Root Mean Square Error (RMSE) of the depth estimates at different distances using four different image resolutions. The results reveal that the depth error has heavy tails, implying that outliers substantially impact accuracy. Hence, depth errors should not be modeled as normally distributed errors. Moreover, only two out of four resolutions provided the capability of acquiring depth data up to 18 m. These insights provide guidelines for understanding the ZED 2i camera's true capabilities, determining its suitability for different applications and environments, and giving baselines for future tests of other competing sensor units. Furthermore, the study offers a simple, inexpensive, and laboratory space-free, yet effective setup that does not need extensive equipment or complex configurations to facilitate the benchmarking of depth cameras in different working environments.</p></div>\",\"PeriodicalId\":49592,\"journal\":{\"name\":\"Robotics and Autonomous Systems\",\"volume\":\"179 \",\"pages\":\"Article 104753\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S0921889024001374/pdfft?md5=78c013418bab605b62edc7c64d077911&pid=1-s2.0-S0921889024001374-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Robotics and Autonomous Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0921889024001374\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Autonomous Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0921889024001374","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Depth accuracy analysis of the ZED 2i Stereo Camera in an indoor Environment
Accurate depth information is crucial for autonomous systems to navigate and interact safely with their surroundings. Passive stereo-vision cameras, such as the ZED 2i, obtain depth information through stereo-image analysis and triangulation. The study measures and assesses the true capabilities of the ZED 2i camera in a real indoor office environment. Furthermore, the study provides a standard test setup to reproduce similar benchmarks with different depth cameras. To achieve the set goals, an experiment was devised and carried out in an office environment to determine the camera depth error and Root Mean Square Error (RMSE) of the depth estimates at different distances using four different image resolutions. The results reveal that the depth error has heavy tails, implying that outliers substantially impact accuracy. Hence, depth errors should not be modeled as normally distributed errors. Moreover, only two out of four resolutions provided the capability of acquiring depth data up to 18 m. These insights provide guidelines for understanding the ZED 2i camera's true capabilities, determining its suitability for different applications and environments, and giving baselines for future tests of other competing sensor units. Furthermore, the study offers a simple, inexpensive, and laboratory space-free, yet effective setup that does not need extensive equipment or complex configurations to facilitate the benchmarking of depth cameras in different working environments.
期刊介绍:
Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems.
Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.