{"title":"创造:户外环境中目标检测的计算约束旅行辅助","authors":"K. Manjari, M. Verma, Gaurav Singal","doi":"10.1109/SITIS.2019.00049","DOIUrl":null,"url":null,"abstract":"In the era of technological advancements, where humans are leveraging it in every sector, it will be highly unfair for the visually impaired to be left off. Hence, this research of developing a compact computational constrained travel aid to help them easily tackle the daily practice is a necessity. As there are approximately 1.3 billion visually impaired people, having a low-cost solution for them is an important requirement. To match this condition, we have used raspberry pi 3 and pi 4 tagged with the pi camera and sonar sensor, all of which are budget-friendly and serves our purpose. This system is attached to a cane and notifies the user about the nature and range of object with the help of sonar sensor and images captured from the pi camera. We have used the lighter versions of You Only Look Once (YOLO) and Single Shot Multibox Detector (SSD) model that has been deployed on both raspberry pi 3 and pi 4. The performance of both versions of raspberry with different models has been tested in an outdoor scenario. It has been observed that raspberry pi 4 is twice faster than pi 3 and the overall performance of Tiny YOLOv3 (Model2) is best in comparison to other models on both pi 3 and pi 4.","PeriodicalId":301876,"journal":{"name":"2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","volume":"16 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"CREATION: Computational ConstRained Travel Aid for Object Detection in Outdoor eNvironment\",\"authors\":\"K. Manjari, M. Verma, Gaurav Singal\",\"doi\":\"10.1109/SITIS.2019.00049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the era of technological advancements, where humans are leveraging it in every sector, it will be highly unfair for the visually impaired to be left off. Hence, this research of developing a compact computational constrained travel aid to help them easily tackle the daily practice is a necessity. As there are approximately 1.3 billion visually impaired people, having a low-cost solution for them is an important requirement. To match this condition, we have used raspberry pi 3 and pi 4 tagged with the pi camera and sonar sensor, all of which are budget-friendly and serves our purpose. This system is attached to a cane and notifies the user about the nature and range of object with the help of sonar sensor and images captured from the pi camera. We have used the lighter versions of You Only Look Once (YOLO) and Single Shot Multibox Detector (SSD) model that has been deployed on both raspberry pi 3 and pi 4. The performance of both versions of raspberry with different models has been tested in an outdoor scenario. It has been observed that raspberry pi 4 is twice faster than pi 3 and the overall performance of Tiny YOLOv3 (Model2) is best in comparison to other models on both pi 3 and pi 4.\",\"PeriodicalId\":301876,\"journal\":{\"name\":\"2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)\",\"volume\":\"16 2\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SITIS.2019.00049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 15th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SITIS.2019.00049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
摘要
在技术进步的时代,人类在各个领域都在利用它,如果视障人士被排除在外,那将是非常不公平的。因此,这项研究开发一个紧凑的计算约束旅行援助,以帮助他们轻松地解决日常实践是必要的。全球约有13亿视障人士,因此为他们提供低成本的解决方案是一项重要要求。为了满足这一条件,我们使用了树莓派3和pi 4,标记有pi相机和声纳传感器,所有这些都是预算友好的,符合我们的目的。该系统连接在一根手杖上,并通过声纳传感器和从pi相机捕获的图像通知用户物体的性质和范围。我们使用了较轻版本的You Only Look Once (YOLO)和Single Shot Multibox Detector (SSD)模型,这些模型已经部署在raspberry pi 3和pi 4上。不同型号的两个版本的树莓的性能已经在室外场景中进行了测试。据观察,raspberry pi 4的速度是pi 3的两倍,而Tiny YOLOv3 (Model2)的整体性能在pi 3和pi 4上都优于其他模型。
CREATION: Computational ConstRained Travel Aid for Object Detection in Outdoor eNvironment
In the era of technological advancements, where humans are leveraging it in every sector, it will be highly unfair for the visually impaired to be left off. Hence, this research of developing a compact computational constrained travel aid to help them easily tackle the daily practice is a necessity. As there are approximately 1.3 billion visually impaired people, having a low-cost solution for them is an important requirement. To match this condition, we have used raspberry pi 3 and pi 4 tagged with the pi camera and sonar sensor, all of which are budget-friendly and serves our purpose. This system is attached to a cane and notifies the user about the nature and range of object with the help of sonar sensor and images captured from the pi camera. We have used the lighter versions of You Only Look Once (YOLO) and Single Shot Multibox Detector (SSD) model that has been deployed on both raspberry pi 3 and pi 4. The performance of both versions of raspberry with different models has been tested in an outdoor scenario. It has been observed that raspberry pi 4 is twice faster than pi 3 and the overall performance of Tiny YOLOv3 (Model2) is best in comparison to other models on both pi 3 and pi 4.