本文選題：計(jì)算機(jī)視覺 + 藝術(shù)體操　； 參考：《現(xiàn)代電子技術(shù)》2017年19期

【摘要】：為了解決傳統(tǒng)基于卡爾曼濾波算法進(jìn)行藝術(shù)體操軌跡跟蹤時(shí)存在的跟蹤漂移以及跟蹤效率低等問題,研究基于計(jì)算機(jī)視覺的藝術(shù)體操軌跡跟蹤方法,通過Vi Be運(yùn)動(dòng)目標(biāo)檢索算法對(duì)圖像的顏色以及深度信息建模,基于圖像顏色以及深度的波動(dòng)檢測出視頻中的運(yùn)動(dòng)目標(biāo),采用KCF算法實(shí)現(xiàn)運(yùn)動(dòng)目標(biāo)的初步跟蹤,在該方法的基礎(chǔ)上,通過改進(jìn)KCF算法解決運(yùn)動(dòng)目標(biāo)被遮擋出現(xiàn)的跟蹤漂移問題,提高運(yùn)動(dòng)目標(biāo)跟蹤的精度和穩(wěn)定性。通過Hermite插值運(yùn)算運(yùn)動(dòng)目標(biāo)質(zhì)心,基于時(shí)刻t的運(yùn)動(dòng)模糊方向獲取瞬時(shí)質(zhì)心軌跡,得到最佳的運(yùn)動(dòng)目標(biāo)質(zhì)心軌跡,采用曲線擬合措施獲取精確的運(yùn)動(dòng)目標(biāo)質(zhì)心軌跡。實(shí)驗(yàn)結(jié)果說明,所提方法可準(zhǔn)確跟蹤藝術(shù)體操運(yùn)動(dòng)軌跡,具有較高的跟蹤效率和穩(wěn)定性。
[Abstract]:In order to solve the problems of track drift and low tracking efficiency in traditional track tracking of rhythmic gymnastics based on Kalman filtering algorithm, the track tracking method of rhythmic gymnastics based on computer vision is studied. The color and depth information of the image is modeled by Vi be moving target retrieval algorithm. Based on the fluctuation of color and depth of the image, the moving object in the video is detected. The KCF algorithm is used to realize the initial tracking of the moving object. On the basis of this method, the tracking drift problem is solved by improved KCF algorithm, which can improve the accuracy and stability of moving target tracking. By Hermite interpolation, the instantaneous centroid trajectory is obtained based on the motion fuzzy direction of time t, and the best trajectory of moving object centroid is obtained, and the accurate trajectory of moving object centroid is obtained by curve fitting. The experimental results show that the proposed method can track the track of rhythmic gymnastics accurately and has high tracking efficiency and stability.
【作者單位】： 重慶三峽學(xué)院;
【分類號(hào)】：G834;TP391.41

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本文編號(hào)：2040223