| 引用本文: | 马琳,赵航,谭学治.基于光流法算法的Visual Map快速建立方法[J].哈尔滨工业大学学报,2017,49(11):24.DOI:10.11918/j.issn.0367-6234.201706026 |
| MA Lin,ZHAO Hang,TAN Xuezhi.Establishing Visual Map rapidly using optical flow technique[J].Journal of Harbin Institute of Technology,2017,49(11):24.DOI:10.11918/j.issn.0367-6234.201706026 |
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| 摘要: |
| Visual Map是一个含有丰富位置信息的图像数据库，数据库中每一幅图片或图片的特征在存储时会加入相应的位置信息.室内定位的性能与Visual Map图片的数量有关.建立庞大的图片数据库能够使得定位结果更加准确，但是花费时间成本会更大.针对这个问题，本文提出了使用光流法算法来建立图片数据库Visual Map.针对光流法用于室内图像的计算会受到光线明暗不同的影响以及相机转向会产生横向偏移的问题，本文对光流法进行了改进，并使用改进后的光流法算法对摄像机采集的图像序列进行计算，得到摄像机的自身位移，从而得到每一幅图片的对应的地理位置信息.实验结果表明，利用使用光流法快速建立的Visual Map进行室内定位，误差小于1米的概率是26%，误差小于2米的概率是70%.与传统的视觉室内定位法相比，定位精度虽然略有降低，但建立图像数据库所需时间消耗大大减少.相比于视频流快速建立Visual Map方法，定位效果相当，建立Visual Map所需的设备更少，要求更加宽松.利用光流法算法快速建立Visual Map能够很好的应用于室内视觉定位系统，特别是应用于大型场所以及室内场景多变化的场所.
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| 关键词: 计算机应用 Visual Map 光流法 室内定位系统 图像数据库 |
| DOI：10.11918/j.issn.0367-6234.201706026 |
| 分类号:tp399 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(61571162); 黑龙江省自然科学基金(F2016019) |
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| Establishing Visual Map rapidly using optical flow technique |
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MA Lin,ZHAO Hang,TAN Xuezhi
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(Communication Research Center, Harbin Institute of Technology, Harbin 150001, China)
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| Abstract: |
| A Visual Map can be seen as an image database with rich location information. All images or image features stored in this database have their corresponding location information. An accurate localization needs a large image database, but building a large database must be laborious and time-consuming. In order to solve this problem, a method based on Optical Flow Technique is proposed to establish a Visual Map. The accuracy of Optical Flow algorithms is always influenced by the difference of indoor illumination and lateral deviation of optical flow caused by turning of the cameras. A method to improve optical flow algorithm is proposed and the new algorithm is used to calculate the displacement of image sequences to acquire location information of the camera and each picture. The experimental results show that the probability of localization error less than 1 meter and 2 meters is 26% and 70%, respectively. Compared with traditional visual indoor localization system, using optical flow algorithm to build a visual map is much more convenient and time-saving, although the positioning accuracy of the proposed method is slightly worse than the traditional method. Although the performance of the proposed method is similar to the video stream method, it needs fewer sensors to build image database and can be used in more complicated environment. Overall, the proposed method will perform well in indoor visual localization systems especially in large buildings and changeable places.
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| Key words: computer application Visual Map optical flow indoor localization system image database |
