无码av一区二区三区无码,在线观看老湿视频福利,日韩经典三级片,成 人色 网 站 欧美大片在线观看

歡迎光臨散文網(wǎng) 會員登陸 & 注冊

特價之四

2023-02-17 15:46 作者:天津正則文創(chuàng)  | 我要投稿

Title:
Machine learning based method for recognition of image to capture motion behavior for sports training
(基于機器學(xué)習(xí)的圖像識別方法捕捉運動訓(xùn)練運動行為)
Abstract:
There is a need to devise intelligent methods for motion based image classification to produce accurate results for the correct judgement. The existing methods cannot use the image block classification method to recognize the motion behavior of antagonistic sports training and it is the need of the hour to devise newer methods for the same. The recognition result is not ideal by using the traditional methods. This paper proposes an image block classification method for antagonistic sports training behavior recognition. It classifies the noise sources, quantifies the influence degree of each noise source effectively and adjusts the noise factor in the de-noising method for different noise sources and the specific weight of different noise sources. The adaptive de-noising of different noise types of antagonistic sports training image sequence is realized. By using the combination of key frame template selection method and image segmentation method for behavior representation, the features are extracted well. The feature extraction is done on the image region according to the proportion of the number of foreground pixels in each block of the template to the number of pixels in the block. The feature vector is used to form the template. Aiming at the behavior representation and feature extraction based on the features of skeleton joint points, image block classification is used to extract the coordinates of skeleton joint points during human movement. K-means clustering is used to transform them into symbol sequence to represent behavior features which is used for antagonistic sports training behavior recognition. Simulation results show that the proposed method can obtain ideal recognition results and it outperforms the existing methods.

期刊:
soft computing
期刊分類:計算機科學(xué),人工智能;跨學(xué)科應(yīng)用
國際刊號:1432-7643
分區(qū):JCR2區(qū)/中科院3區(qū)
影響因子:3.731
檢索:SCIE
出版版面:???br>出版社:SPRINGER

特價之四的評論 (共 條)

分享到微博請遵守國家法律
静乐县| 新民市| 蓬莱市| 瓮安县| 达孜县| 岑溪市| 井冈山市| 寿阳县| 平乡县| 铜陵市| 贵定县| 朝阳县| 西吉县| 南江县| 兰溪市| 吕梁市| 营山县| 东乡族自治县| 赤峰市| 临洮县| 大港区| 辽宁省| 积石山| 恩平市| 民和| 多伦县| 繁昌县| 高雄县| 商河县| 闻喜县| 江口县| 孙吴县| 广汉市| 景谷| 枞阳县| 绥芬河市| 锦屏县| 马鞍山市| 诸暨市| 平定县| 上高县|