本文選題：室內(nèi)定位 + 手機傳感器��； 參考：《地球信息科學(xué)學(xué)報》2017年06期

【摘要】：商業(yè)和工業(yè)領(lǐng)域中,室內(nèi)行人、車輛、機器人的位置信息正逐漸成為人們關(guān)注的熱點,并隨之產(chǎn)生了大量的室內(nèi)定位技術(shù)和方法,如使用無線信號、地磁、超寬帶和超聲波等方式進行室內(nèi)定位。然而,目前的這些室內(nèi)定位方法大多需要額外輔助設(shè)備的支撐,增加了定位成本和硬件開銷。視覺定位作為一種目前較為流行的定位方式,具有實施成本低、不依賴任何外界輔助設(shè)備等優(yōu)勢。其中,構(gòu)建帶有位置標簽的圖像數(shù)據(jù)庫是視覺定位方法的關(guān)鍵環(huán)節(jié),而傳統(tǒng)的構(gòu)建圖像數(shù)據(jù)庫方法人力開銷大、時耗長。因此,本文提出一種運動恢復(fù)結(jié)構(gòu)(SFM)和航位推算結(jié)合的視覺定位方法,能夠快速構(gòu)建圖像位置數(shù)據(jù)庫、大大降低人力開銷。該方法主要包括2個階段:離線階段和在線階段。離線階段主要實現(xiàn)圖像序列位置的自動標注,通過采集行走路線上的手機內(nèi)置傳感器信息和視頻信息,提出一種多約束圖像匹配方法用于視頻圖像的連續(xù)匹配,將匹配結(jié)果用于SFM方法,可以得到相鄰圖像間的運動角度,使用行人航位推算(PDR)方法標注圖像序列的軌跡坐標。在線階段使用提出的圖像匹配方法計算查詢圖像與數(shù)據(jù)庫影像間的匹配點數(shù)量,將匹配點最多的K個數(shù)據(jù)庫影像位置坐標加權(quán)平均作為查詢圖像的定位結(jié)果。最后,分別在2種典型的室內(nèi)環(huán)境下進行實驗,結(jié)果表明本文方法在離線階段位置標注的平均誤差為0.58 m,在線階段圖像匹配定位的誤差范圍在0.2~1.4 m。
[Abstract]:In the commercial and industrial fields, the position information of indoor pedestrian, vehicle and robot is gradually becoming the focus of attention, and a large number of indoor positioning techniques and methods have been generated, such as the use of wireless signals, geomagnetic, Ultra-wideband and ultrasonic wave and other methods for indoor positioning. However, most of these indoor positioning methods need the support of additional auxiliary equipment, which increases the location cost and hardware cost. As a popular positioning method, visual positioning has the advantages of low implementation cost and no dependence on any external auxiliary equipment. Among them, the construction of image database with location label is the key link of the visual positioning method, while the traditional method of building image database has a large human cost and time consuming. Therefore, this paper proposes a visual location method combining motion recovery structure (SFM) with dead-reckoning, which can quickly construct image location database and greatly reduce manpower cost. The method mainly includes two stages: offline and online. In the off-line stage, the automatic tagging of image sequence position is realized. By collecting sensor information and video information from mobile phone, a multi-constraint image matching method is proposed for continuous video image matching. Applying the matching results to SFM method, the motion angle between adjacent images can be obtained, and the track coordinates of image sequences can be marked by using the method of pedestrian carrier reckoning (PDR). In the online stage, the number of matching points between the query image and the database image is calculated by using the proposed image matching method, and the weighted average of the location of K database images with the most matching points is taken as the location result of the query image. Finally, experiments are carried out in two typical indoor environments. The results show that the average error of the method is 0.58 m in off-line phase and 0.21.4 m in online stage.
【作者單位】： 深圳大學(xué)土木工程學(xué)院深圳市空間信息智能感知與服務(wù)重點實驗室;河南財經(jīng)政法大學(xué)資環(huán)與環(huán)境學(xué)院;武漢大學(xué)測繪遙感信息工程國家重點實驗室;中山大學(xué)地理科學(xué)與規(guī)劃學(xué)院綜合地理信息研究中心;
【基金】：國家自然科學(xué)基金項目(41301511、41371377、41371420、41501424) 國家重點研發(fā)計劃項目(2016YFB0502203) 深圳市科技計劃項目(JCYJ20140418095735587) 深圳大學(xué)科研啟動基金資助項目(2016064)
【分類號】：TP391.41

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