本文選題：手勢識別 + 邊緣序列�。� 參考：《計算機輔助設(shè)計與圖形學(xué)學(xué)報》2017年04期

【摘要】：針對傳統(tǒng)手勢識別準(zhǔn)確率不高、魯棒性不強的問題,通過研究靜態(tài)手勢輪廓特征,從手勢邊緣序列角度出發(fā)提出一種基于手勢邊緣輪廓遞歸圖的CK-1距離的手勢識別算法CSRP.首先通過閾值分割獲取手勢區(qū)域圖像;然后定位起始點坐標(biāo),建立隨著空間位置變化的手勢邊緣序列;為了克服邊緣序列數(shù)據(jù)的不等長問題,構(gòu)造基于時空域的手勢輪廓序列遞歸圖;最后利用MPEG-1壓縮算法計算手勢遞歸圖像之間的CK-1距離,完成手勢識別.實驗結(jié)果表明,該算法在手勢發(fā)生旋轉(zhuǎn)、平移、縮放時具有較高的魯棒性,并且計算量小、效率高,手勢識別的準(zhǔn)確率高達97%.
[Abstract]:Aiming at the problem that the accuracy and robustness of traditional gesture recognition are not high, a gesture recognition algorithm based on CK-1 distance based on gesture edge recursive graph is proposed by studying the static gesture contour features and starting from the angle of gesture edge sequence. First, the gesture region image is obtained by threshold segmentation; then, the starting point coordinate is located, and the gesture edge sequence with spatial position is established. In order to overcome the unequal length of edge sequence data, Finally, the MPEG-1 compression algorithm is used to calculate the CK-1 distance between the gesture recursion images to complete the gesture recognition. The experimental results show that the algorithm is robust when the gesture is rotated, translated and scaled, and the computation is small, the efficiency is high, and the accuracy of gesture recognition is as high as 97%.
【作者單位】： 西北大學(xué)信息科學(xué)與技術(shù)學(xué)院;
【基金】：國家自然科學(xué)基金(61305032) 陜西省教育廳科學(xué)研究計劃項目(15JK1689)
【分類號】：TP391.41

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