The concept of self-healing that involves a built-in ability to heal in response to damage wherever and whenever it occurs in a material,analogous to the healing process in living organisms,has emerged a couple of dec...The concept of self-healing that involves a built-in ability to heal in response to damage wherever and whenever it occurs in a material,analogous to the healing process in living organisms,has emerged a couple of decades ago.Driven primarily by the demands for life-like materials and soft smart materials,therefore,the development of self-healing polymeric hydrogels has continually attracted the attention of the scientific community.Here,this review is intended to give an in-depth overview of the state-of-the-art advances in the field of self-healing polymeric hydrogels.Specifically,recently emerging trends in self-healing polymeric hydrogels are summarized,and notably,recommendations to endow these hydrogels with fascinating multi-functionalities including luminescence,conductivity/magnetism and shape memory etc are presented.To close,the current challenges and future opportunities in this field are also discussed.展开更多
We propose a framework of hand articulation detection from a monocular depth image using curvature scale space(CSS) descriptors. We extract the hand contour from an input depth image, and obtain the fingertips and fin...We propose a framework of hand articulation detection from a monocular depth image using curvature scale space(CSS) descriptors. We extract the hand contour from an input depth image, and obtain the fingertips and finger-valleys of the contour using the local extrema of a modified CSS map of the contour. Then we recover the undetected fingertips according to the local change of depths of points in the interior of the contour. Compared with traditional appearance-based approaches using either angle detectors or convex hull detectors, the modified CSS descriptor extracts the fingertips and finger-valleys more precisely since it is more robust to noisy or corrupted data;moreover, the local extrema of depths recover the fingertips of bending fingers well while traditional appearance-based approaches hardly work without matching models of hands. Experimental results show that our method captures the hand articulations more precisely compared with three state-of-the-art appearance-based approaches.展开更多
基金supported by the National Natural Science Foundation of China(Nos.51773215,21774138)the Sino-German Mobility Programme(No.M-0424)+4 种基金Key Research Program of Frontier Sciences,Chinese Academy of Sciences(No.QYZDB-SSW-SLH036)Youth Innovation Promotion Association of Chinese Academy of Sciences(No.2019297)Xiaoling Zuo is grateful for the financial supported by Science and Technology Fund of Guizhou Provinee,China(No.[2020]1 Y209)the Overseas Talents Selection Fund of Guizhou Province,China(No.[2020]11)Fund Project of Guizhou Minzu University,China(No.GZMU[2019]YB23).
文摘The concept of self-healing that involves a built-in ability to heal in response to damage wherever and whenever it occurs in a material,analogous to the healing process in living organisms,has emerged a couple of decades ago.Driven primarily by the demands for life-like materials and soft smart materials,therefore,the development of self-healing polymeric hydrogels has continually attracted the attention of the scientific community.Here,this review is intended to give an in-depth overview of the state-of-the-art advances in the field of self-healing polymeric hydrogels.Specifically,recently emerging trends in self-healing polymeric hydrogels are summarized,and notably,recommendations to endow these hydrogels with fascinating multi-functionalities including luminescence,conductivity/magnetism and shape memory etc are presented.To close,the current challenges and future opportunities in this field are also discussed.
基金supported by the National Natural Science Foundation of China(Nos.6122700461370120+5 种基金6139051061300065and 61402024)Beijing Municipal Natural Science Foundation,China(No.4142010)Beijing Municipal Commission of Education,China(No.km201410005013)the Funding Project for Academic Human Resources Development in Institutions of Higher Learning under the Jurisdiction of Beijing Municipality,China
文摘We propose a framework of hand articulation detection from a monocular depth image using curvature scale space(CSS) descriptors. We extract the hand contour from an input depth image, and obtain the fingertips and finger-valleys of the contour using the local extrema of a modified CSS map of the contour. Then we recover the undetected fingertips according to the local change of depths of points in the interior of the contour. Compared with traditional appearance-based approaches using either angle detectors or convex hull detectors, the modified CSS descriptor extracts the fingertips and finger-valleys more precisely since it is more robust to noisy or corrupted data;moreover, the local extrema of depths recover the fingertips of bending fingers well while traditional appearance-based approaches hardly work without matching models of hands. Experimental results show that our method captures the hand articulations more precisely compared with three state-of-the-art appearance-based approaches.
