發(fā)布時(shí)間：2018-05-15 13:36

  本文選題：行人再識(shí)別 + 支持樣本��； 參考：《電子與信息學(xué)報(bào)》2017年12期

【摘要】：行人再識(shí)別就是在無(wú)重疊視域多攝像機(jī)監(jiān)控系統(tǒng)中,識(shí)別出相同的行人。針對(duì)來(lái)自于不同攝像頭行人圖片存在著視角、光照和尺度變化的問(wèn)題。該文提出了基于支持樣本間接式匹配的行人再識(shí)別方法。該算法首先通過(guò)聚類(lèi)的方法分別提取不同攝像頭下的支持樣本,當(dāng)要對(duì)來(lái)自不同攝像頭的行人進(jìn)行匹配時(shí),在距離測(cè)度的基礎(chǔ)上利用支持樣本分別判別出其所在攝像頭下的行人類(lèi)別,通過(guò)類(lèi)別的對(duì)比判斷是否為同一行人。該方法避免了不同攝像頭下行人圖片直接匹配,有效解決不同攝像頭帶來(lái)的視角、光照和尺度問(wèn)題。實(shí)驗(yàn)結(jié)果表明該文的算法相比一些經(jīng)典算法識(shí)別率有一定的提高,并且在數(shù)據(jù)集VIPe R,CAVIAR4Re ID和CUHK01上,Rank1分別達(dá)到了43.60%,41.36%,43.82%。
[Abstract]:Pedestrian recognition is to identify the same pedestrian in a multi-camera surveillance system. There are problems in view, illumination and scale change of pedestrian images from different cameras. In this paper, a pedestrian recognition method based on support sample indirect matching is proposed. The algorithm firstly extracts support samples from different cameras by clustering method, and then matches pedestrians from different cameras. On the basis of distance measure, the support samples are used to identify the pedestrian category under the camera, and to judge whether the pedestrian is the same pedestrian by the comparison of the categories. This method avoids the direct matching of downlink images of different cameras, and effectively solves the problems of angle of view, illumination and scale brought by different cameras. The experimental results show that the recognition rate of the proposed algorithm is higher than that of some classical algorithms, and the Rank1 is 43.60 and 43.82 on the data set VIPe RnCAVIAR4Re ID and CUHK01, respectively.
【作者單位】： 合肥工業(yè)大學(xué)計(jì)算機(jī)與信息學(xué)院;工業(yè)安全與應(yīng)急技術(shù)安徽省重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金(61471154) 安徽省科技攻關(guān)科技強(qiáng)警項(xiàng)目(170d0802181)~~
【分類(lèi)號(hào)】：TP391.41

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1 張巖;基于單目攝像頭三維估計(jì)的車(chē)型識(shí)別方法研究[D];西安理工大學(xué);2017年

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