基于光流法算法的Visual Map快速建立方法
發(fā)布時間:2018-08-22 13:16
【摘要】:Visual Map是一個含有豐富位置信息的圖像數(shù)據(jù)庫,數(shù)據(jù)庫中每一幅圖片或圖片的特征在存儲時會加入相應(yīng)的位置信息.室內(nèi)定位的性能與Visual Map圖片的數(shù)量有關(guān).建立龐大的圖片數(shù)據(jù)庫能夠使得定位結(jié)果更加準確,但是花費時間成本會更大.針對這個問題,本文提出了使用光流法算法來建立圖片數(shù)據(jù)庫Visual Map.針對光流法用于室內(nèi)圖像的計算會受到光線明暗不同的影響以及相機轉(zhuǎn)向會產(chǎn)生橫向偏移的問題,本文對光流法進行了改進,并使用改進后的光流法算法對攝像機采集的圖像序列進行計算,得到攝像機的自身位移,從而得到每一幅圖片的對應(yīng)的地理位置信息.實驗結(jié)果表明,利用使用光流法快速建立的Visual Map進行室內(nèi)定位,誤差小于1米的概率是26%,誤差小于2米的概率是70%.與傳統(tǒng)的視覺室內(nèi)定位法相比,定位精度雖然略有降低,但建立圖像數(shù)據(jù)庫所需時間消耗大大減少.相比于視頻流快速建立Visual Map方法,定位效果相當(dāng),建立Visual Map所需的設(shè)備更少,要求更加寬松.利用光流法算法快速建立Visual Map能夠很好的應(yīng)用于室內(nèi)視覺定位系統(tǒng),特別是應(yīng)用于大型場所以及室內(nèi)場景多變化的場所.
[Abstract]:Visual Map is an image database with abundant location information. Each picture or image feature in the database will be stored with the corresponding location information. The performance of indoor positioning is related to the number of Visual Map images. A large database of images can make the location more accurate, but it will take more time and cost. In order to solve this problem, an optical flow algorithm is proposed to build the image database Visual Map. In view of the problem that the calculation of indoor images by optical flow method will be affected by different light and dark light and the lateral deviation of camera steering will occur, the optical flow method is improved in this paper. The improved optical flow algorithm is used to calculate the sequence of images collected by the camera, and the displacement of the camera itself is obtained, and the corresponding geographic position information of each picture is obtained. The experimental results show that the probability of the error less than 1 meter is 26 and the probability of error less than 2 meters is 70. Compared with the traditional visual indoor positioning method, the positioning accuracy is slightly reduced, but the time consumption to establish the image database is greatly reduced. Compared with the fast Visual Map method of video stream, the location effect is equal, the equipment needed to establish Visual Map is less, and the requirement is more relaxed. Using the optical flow algorithm to quickly establish Visual Map can be used in indoor visual positioning system, especially in large places and places where the indoor scene changes.
【作者單位】: 哈爾濱工業(yè)大學(xué)通信技術(shù)研究所;
【基金】:國家自然科學(xué)基金(61571162) 黑龍江省自然科學(xué)基金(F2016019)
【分類號】:TP311.13;TP391.41
[Abstract]:Visual Map is an image database with abundant location information. Each picture or image feature in the database will be stored with the corresponding location information. The performance of indoor positioning is related to the number of Visual Map images. A large database of images can make the location more accurate, but it will take more time and cost. In order to solve this problem, an optical flow algorithm is proposed to build the image database Visual Map. In view of the problem that the calculation of indoor images by optical flow method will be affected by different light and dark light and the lateral deviation of camera steering will occur, the optical flow method is improved in this paper. The improved optical flow algorithm is used to calculate the sequence of images collected by the camera, and the displacement of the camera itself is obtained, and the corresponding geographic position information of each picture is obtained. The experimental results show that the probability of the error less than 1 meter is 26 and the probability of error less than 2 meters is 70. Compared with the traditional visual indoor positioning method, the positioning accuracy is slightly reduced, but the time consumption to establish the image database is greatly reduced. Compared with the fast Visual Map method of video stream, the location effect is equal, the equipment needed to establish Visual Map is less, and the requirement is more relaxed. Using the optical flow algorithm to quickly establish Visual Map can be used in indoor visual positioning system, especially in large places and places where the indoor scene changes.
【作者單位】: 哈爾濱工業(yè)大學(xué)通信技術(shù)研究所;
【基金】:國家自然科學(xué)基金(61571162) 黑龍江省自然科學(xué)基金(F2016019)
【分類號】:TP311.13;TP391.41
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