计算机工程与应用
計算機工程與應用
계산궤공정여응용
COMPUTER ENGINEERING AND APPLICATIONS
2014年
6期
165-170
,共6页
人脸识别%动态时间规整%局部分块匹配%查询人脸%探针图像
人臉識彆%動態時間規整%跼部分塊匹配%查詢人臉%探針圖像
인검식별%동태시간규정%국부분괴필배%사순인검%탐침도상
face recognition%dynamic time warping%local partitioned matching%query face%probe image
针对现实人脸识别中姿势、光照、表情变化及遮挡等严重影响识别性能的问题,提出了一种基于动态时间规整优化局部分块匹配的户外人脸识别算法。将人脸图像划分成若干大小相等且互不重叠的局部小块;借助于光栅扫描顺序将各个小块按照前额、眼睛、鼻子、嘴巴和下巴的顺序连接成一个单一序列;计算查询人脸与注册人脸之间图像到类的距离,利用动态时间规整的设计思想寻找查询序列与所有注册序列之间的最佳对齐方式。在三个公开人脸数据库LFW、AR及YouTube上的实验验证了该方法的有效性及可靠性,实验结果表明,相比其他几种较为先进的人脸识别方法,该方法取得了更高的识别率,此外,该方法无需任何训练过程,计算成本低。
針對現實人臉識彆中姿勢、光照、錶情變化及遮擋等嚴重影響識彆性能的問題,提齣瞭一種基于動態時間規整優化跼部分塊匹配的戶外人臉識彆算法。將人臉圖像劃分成若榦大小相等且互不重疊的跼部小塊;藉助于光柵掃描順序將各箇小塊按照前額、眼睛、鼻子、嘴巴和下巴的順序連接成一箇單一序列;計算查詢人臉與註冊人臉之間圖像到類的距離,利用動態時間規整的設計思想尋找查詢序列與所有註冊序列之間的最佳對齊方式。在三箇公開人臉數據庫LFW、AR及YouTube上的實驗驗證瞭該方法的有效性及可靠性,實驗結果錶明,相比其他幾種較為先進的人臉識彆方法,該方法取得瞭更高的識彆率,此外,該方法無需任何訓練過程,計算成本低。
침대현실인검식별중자세、광조、표정변화급차당등엄중영향식별성능적문제,제출료일충기우동태시간규정우화국부분괴필배적호외인검식별산법。장인검도상화분성약간대소상등차호불중첩적국부소괴;차조우광책소묘순서장각개소괴안조전액、안정、비자、취파화하파적순서련접성일개단일서렬;계산사순인검여주책인검지간도상도류적거리,이용동태시간규정적설계사상심조사순서렬여소유주책서렬지간적최가대제방식。재삼개공개인검수거고LFW、AR급YouTube상적실험험증료해방법적유효성급가고성,실험결과표명,상비기타궤충교위선진적인검식별방법,해방법취득료경고적식별솔,차외,해방법무수임하훈련과정,계산성본저。
Large variation of pose, illustration, expression and occlusion in truly face recognition will seriously impact recognition performance, for which Local Partition Matching(LPM) algorithm optimized by Dynamic Time Warping (DTW)is proposed. Face image is divided into many non-overlapping patches with same size. All patches are combined to be a unique sequence sorting by forehead, eyes, nose, mouth and chin by using raster scan sequence. Distance from im-age to class between query face and register faces is calculated, and idea of DTW is used to find the best alignment be-tween query sequence and all register sequences. The effectiveness and reliability of proposed method have been verified by experiments on the three common databases LFW, AR and YouTube. Experimental results show that proposed method has higher recognition accuracy than several advanced face recognition methods. Besides, it has lower cost without any training process.