本文選題：行人再識(shí)別 + 分塊匹配��； 參考：《計(jì)算機(jī)應(yīng)用研究》2017年04期

【摘要】：針對(duì)行人再識(shí)別精度低的難題進(jìn)行研究,提出了一種新的基于分塊匹配的行人再識(shí)別方法。首先,引入帶人體結(jié)構(gòu)信息的人體DPM對(duì)行人外觀進(jìn)行分割,得到的帶語(yǔ)義信息的身體部件作為匹配識(shí)別的基本單元;其次,基于深度神經(jīng)網(wǎng)絡(luò)模型提取各部件的深度特征作為匹配依據(jù);再次,基于余弦距離判斷各身體部件與目標(biāo)行人對(duì)應(yīng)部件的相似性;最后,融合所有身體部件的識(shí)別結(jié)果得到最終的再識(shí)別結(jié)果。實(shí)驗(yàn)結(jié)果表明,跟已有方法相比,該方法具有更好的魯棒性,在識(shí)別精度上有較明顯的優(yōu)勢(shì)。
[Abstract]:A new method of pedestrian rerecognition based on block matching is proposed to solve the problem of low accuracy of pedestrian rerecognition. Firstly, the human body DPM with human structure information is introduced to segment the appearance of pedestrians, and the body parts with semantic information are used as the basic unit of matching recognition. Based on the depth neural network model to extract the depth features of each component as the matching basis; thirdly, based on the cosine distance to judge the similarity between the body parts and the target pedestrian corresponding parts; finally, Fusion of all body parts of the recognition results to obtain the final recognition results. The experimental results show that the proposed method is more robust than the existing methods and has obvious advantages in recognition accuracy.
【作者單位】： 國(guó)家數(shù)字交換系統(tǒng)工程技術(shù)研究中心;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(61521003,61379151) 國(guó)家科技支撐計(jì)劃資助項(xiàng)目(2014BAH30B01) 河南省杰出青年基金資助項(xiàng)目(144100510001)
【分類號(hào)】：TP391.41;TP183
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本文編號(hào)：1823915