Cascaded hand pose regression
Refereed conference paper presented and published in conference proceedings

香港中文大學研究人員
替代計量分析
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其它資訊
摘要We extends the previous 2D cascaded object pose regression work [9] in two aspects so that it works better for 3D articulated objects. Our first contribution is 3D pose-indexed features that generalize the previous 2D parameterized features and achieve better invariance to 3D transformations. Our second contribution is a principled hierarchical regression that is adapted to the articulated object structure. It is therefore more accurate and faster. Comprehensive experiments verify the state-of-the-art accuracy and efficiency of the proposed approach on the challenging 3D hand pose estimation problem, on a public dataset and our new dataset.
著者Sun X., Wei Y., Liang S., Tang X., Sun J.
會議名稱IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
會議開始日07.06.2015
會議完結日12.06.2015
會議地點Boston
會議國家/地區美國
出版年份2015
月份10
日期14
卷號07-12-June-2015
頁次824 - 832
國際標準書號9781467369640
國際標準期刊號1063-6919
語言英式英語

上次更新時間 2020-31-07 於 23:10