针对越来越多的年轻人使用电脑进行办公的时间越来越长,坐姿不正确导致的颈肩腰部疾病发病率及视力下降的问题,设计了一种不需要额外佩戴智能硬件的坐姿检测技术。该方案使用Intel最新的Real Sense 3D摄像头进行画面采集,通过对三维数...针对越来越多的年轻人使用电脑进行办公的时间越来越长,坐姿不正确导致的颈肩腰部疾病发病率及视力下降的问题,设计了一种不需要额外佩戴智能硬件的坐姿检测技术。该方案使用Intel最新的Real Sense 3D摄像头进行画面采集,通过对三维数据的实时分析,准确的判断出用户的坐姿情况,相对于智能硬件的解决方案可以大幅度提高准确度,市场上新出的笔记本电脑中带有Real Sense的型号也较多,具有较好的应用前景。展开更多
该设计是基于Intel Real Sense的物品展示系统的研究与实现,这里的展示系统主要是展示汽车模型的外观,内部结构,汽车和汽车展厅形成一个三维空间并且汽车和汽车展厅都是动态的,通过手部的动作来实现基本的控制,包括打开车门观看车内的结...该设计是基于Intel Real Sense的物品展示系统的研究与实现,这里的展示系统主要是展示汽车模型的外观,内部结构,汽车和汽车展厅形成一个三维空间并且汽车和汽车展厅都是动态的,通过手部的动作来实现基本的控制,包括打开车门观看车内的结构,让你有一种身临其境的感觉,感觉真实地站在展厅里面欣赏汽车。展开更多
Non-destructive plant growth parameters measurement is an important concern in automatic-seedling transplanting.Recently,several image-basedmonitoring approaches have been proposed and potentially developed for severa...Non-destructive plant growth parameters measurement is an important concern in automatic-seedling transplanting.Recently,several image-basedmonitoring approaches have been proposed and potentially developed for several agricultural applications.The presented study proposed and developed a RealSense-based machine vision system for the close-shot seedling-lump integrated monitoring.The strategy was based on the close-shot depth information.Further,the point cloud clustering and suitable algorithms were applied to obtain the segmentation of 3D seedling models.In addition,the data processing pipeline was developed to assess the differentmorphological parameter of 4 different seedling varieties.The experiments were carried out with 4 different seedling varieties(pepper,tomato,cucumber,and lettuce)and trained under different light conditions(light and dark).Moreover,analysis results showed that therewas not significantly different(p<0.05)found towards light and dark environments due to close-shot near-infrared detection.However,the results revealed that the stem diameter relationship between RealSense and the manual method was found for R^2=0.68 cucumber,R^2=0.54 tomato,R^2=0.35 pepper,and R^2=0.58 lettuce seedlings.Whereas,the seedling height relationship between RealSense and the manual methodwas found higher than R^2=0.99,0.99,0.99,and 0.99 for pepper,tomato,cucumber,and lettuce,respectively.Based on the experiment results,it was concluded that the RGB-D integrated monitoring system with the purposed method could be practiced for nursery seedlings most promisingly without high labour requirements in terms of ease of use.The system revealed a good sturdiness and relevance for plant growth monitoring.Additionally,it has the perspective for future practical value to real-time vision servo operations for transplanting robots.展开更多
文摘针对越来越多的年轻人使用电脑进行办公的时间越来越长,坐姿不正确导致的颈肩腰部疾病发病率及视力下降的问题,设计了一种不需要额外佩戴智能硬件的坐姿检测技术。该方案使用Intel最新的Real Sense 3D摄像头进行画面采集,通过对三维数据的实时分析,准确的判断出用户的坐姿情况,相对于智能硬件的解决方案可以大幅度提高准确度,市场上新出的笔记本电脑中带有Real Sense的型号也较多,具有较好的应用前景。
文摘该设计是基于Intel Real Sense的物品展示系统的研究与实现,这里的展示系统主要是展示汽车模型的外观,内部结构,汽车和汽车展厅形成一个三维空间并且汽车和汽车展厅都是动态的,通过手部的动作来实现基本的控制,包括打开车门观看车内的结构,让你有一种身临其境的感觉,感觉真实地站在展厅里面欣赏汽车。
基金Theworkwas supported by grants fromthe Jiangsu Agricultural Science and Technology Innovation Fund(CX(16)1044)the Natural Science Foundation of Colleges in Jiangsu Province(16KJA210002)+1 种基金the Project of Six Talent Peaks in Jiangsu Province(JXQC-008)a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD-2018-87).
文摘Non-destructive plant growth parameters measurement is an important concern in automatic-seedling transplanting.Recently,several image-basedmonitoring approaches have been proposed and potentially developed for several agricultural applications.The presented study proposed and developed a RealSense-based machine vision system for the close-shot seedling-lump integrated monitoring.The strategy was based on the close-shot depth information.Further,the point cloud clustering and suitable algorithms were applied to obtain the segmentation of 3D seedling models.In addition,the data processing pipeline was developed to assess the differentmorphological parameter of 4 different seedling varieties.The experiments were carried out with 4 different seedling varieties(pepper,tomato,cucumber,and lettuce)and trained under different light conditions(light and dark).Moreover,analysis results showed that therewas not significantly different(p<0.05)found towards light and dark environments due to close-shot near-infrared detection.However,the results revealed that the stem diameter relationship between RealSense and the manual method was found for R^2=0.68 cucumber,R^2=0.54 tomato,R^2=0.35 pepper,and R^2=0.58 lettuce seedlings.Whereas,the seedling height relationship between RealSense and the manual methodwas found higher than R^2=0.99,0.99,0.99,and 0.99 for pepper,tomato,cucumber,and lettuce,respectively.Based on the experiment results,it was concluded that the RGB-D integrated monitoring system with the purposed method could be practiced for nursery seedlings most promisingly without high labour requirements in terms of ease of use.The system revealed a good sturdiness and relevance for plant growth monitoring.Additionally,it has the perspective for future practical value to real-time vision servo operations for transplanting robots.