AVI
The following videoes use the video streaming completion model, which combines static and dynamic information for real-time processing. The proposed model is solved using the alternating direction method of multipliers (ADMM), and using MATLAB for solution recovery.
Gray video suzie: This video is restored in the case of the missing rates set to 70%, 80%, 90%, respectively
Color Video Hall: This video is restored in the case of the missing rates set to 70%, 80%, and 90%, respectively
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Grasp intention recognition is a vital problem for controlling assistive robots to help the elderly and infirm people restore arm and hand function. This dataset contains gaze data and scene image data of healthy individuals and hemiplegic patients while performing different grasping tasks. It can be used for gaze-based grasp intention recognition studies.
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“Video Demo” provides the video demo of the implemented prototype system as stated in our manuscript "Blockchain and IoT for Insurance: A Case Study and Cyberinfrastructure Solution on Fine-grained Transportation Insurance"
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It is possible to construct "aerosol cytometers" based on different types of Zhulanov's laser aerosol counters | diffusion aerosol spectrometers (DAS) [1-8] and "hydrosol cytometers" based on hydrosol particle counters (adopted for ocean marine, ocean and hydrothermal conditions [9,10]).
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The image displays four segments of gestures from our dataset.
(a) The video sequence of rotating the wrist down and up as a signal for starting a new gesture.
(b)–(d) Three gestures samples (the triangle, letter b, and letter Z) taken from three different subjects at three different scenes (sitting at a desk, standing indoors, and standing outdoors.). The trajectory of each gesture canbe recognized from the movement of the background objects.
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