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Survey on depth and RGB image-based 3D hand shape and pose estimation 被引量:1
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作者 Lin HUANG Boshen ZHANG +3 位作者 Zhilin GUO Yang XIAO Zhiguo CAO junsong yuan 《Virtual Reality & Intelligent Hardware》 2021年第3期207-234,共28页
The field of vision-based human hand three-dimensional(3D)shape and pose estimation has attracted significant attention recently owing to its key role in various applications,such as natural human computer interaction... The field of vision-based human hand three-dimensional(3D)shape and pose estimation has attracted significant attention recently owing to its key role in various applications,such as natural human computer interactions.With the availability of large-scale annotated hand datasets and the rapid developments of deep neural networks(DNNs),numerous DNN-based data-driven methods have been proposed for accurate and rapid hand shape and pose estimation.Nonetheless,the existence of complicated hand articulation,depth and scale ambiguities,occlusions,and finger similarity remain challenging.In this study,we present a comprehensive survey of state-of-the-art 3D hand shape and pose estimation approaches using RGB-D cameras.Related RGB-D cameras,hand datasets,and a performance analysis are also discussed to provide a holistic view of recent achievements.We also discuss the research potential of this rapidly growing field. 展开更多
关键词 Hand survey 3D hand pose estimation Hand shape reconstruction Hand-object interactions RGB-D cameras
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