کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9952240 | 1444170 | 2018 | 20 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Vision-based human grasp reconstruction inspired by hand postural synergies
ترجمه فارسی عنوان
بازسازی درک انسانی مبتنی بر دیدگاه با الهام از هماهنگی های موضعی موضعی
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی
The human hand exhibits enormous versatility and dexterity, to a degree paralleled by few gripping assemblies. Although several hand posture animators have been discovered, vision-based trackers have retained the research focus owing to their compactness, cost-effectiveness and ease-of-installation. The present investigation explores a marker-based hand pose-tracking solution, using a Kinect depth-capture device. It exploits the inherent synergism within the finger linkages through a novel motion capture algorithm for grasp reclamation. The tracked data-set is analysed for an optimal number of condensed primitives which yielded an effectively reclaimed grasp-pose. Isomap based dimensional reduction followed by Principal Component Analysis (PCA) back-projection, drives the reconstruction of thirty-three Feix-grasps solely from Index, Thumb and three edges of a Palm marker. The derivatives were observed to contribute across grasp initiation to final posture assumption, with a scope for future investigations on their direct correlations to cortical motor impulses.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Electrical Engineering - Volume 70, August 2018, Pages 702-721
Journal: Computers & Electrical Engineering - Volume 70, August 2018, Pages 702-721
نویسندگان
Ritwik Chattaraj, Siladitya Khan, Deepon Ghose Roy, Bikash Bepari, Subhasis Bhaumik,