Space-Variant Image Deblurring on Smartphones Using Inertial Sensors

2014 ◽  
Author(s):  
Ondrej Sindelar ◽  
Filip Sroubek ◽  
Peyman Milanfar
Keyword(s):  
Inertial Sensors ◽  
Image Deblurring ◽  
Space Variant

Image Deblurring Utilizing Inertial Sensors and a Short-Long-Short Exposure Strategy

2020 ◽  
Vol 29 ◽  
pp. 4614-4626
Author(s):  
Chenwei Yang ◽  
Huajun Feng ◽  
Zhihai Xu ◽  
Yueting Chen ◽  
Qi Li
Keyword(s):  
Inertial Sensors ◽  
Image Deblurring ◽  
Short Exposure

scholarly journals Measure and model a 3-D space-variant PSF for fluorescence microscopy image deblurring

2018 ◽  
Vol 26 (11) ◽  
pp. 14375 ◽  
Author(s):  
Yemeng Chen ◽  
Mengmeng Chen ◽  
Li Zhu ◽  
Jane Y. Wu ◽  
Sidan Du ◽  
...  
Keyword(s):  
Fluorescence Microscopy ◽  
Image Deblurring ◽  
Microscopy Image ◽  
Space Variant

Disparity-based space-variant image deblurring

2013 ◽  
Vol 28 (7) ◽  
pp. 792-808 ◽  
Author(s):  
Changsoo Je ◽  
Hyeon Sang Jeon ◽  
Chang-Hwan Son ◽  
Hyung-Min Park
Keyword(s):  
Image Deblurring ◽  
Space Variant

Deadlift Recognition and Application based on Multiple Modalities using Recurrent Neural Network

2020 ◽  
Vol 2020 (17) ◽  
pp. 2-1-2-6
Author(s):  
Shih-Wei Sun ◽  
Ting-Chen Mou ◽  
Pao-Chi Chang
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Network Structure ◽  
Inertial Sensors ◽  
Body Movement ◽  
The Body ◽  
Body Parts ◽  
Multimodal Sensing ◽  
Multiple Devices ◽  
Neural Network Structure

To improve the workout efficiency and to provide the body movement suggestions to users in a “smart gym” environment, we propose to use a depth camera for capturing a user’s body parts and mount multiple inertial sensors on the body parts of a user to generate deadlift behavior models generated by a recurrent neural network structure. The contribution of this paper is trifold: 1) The multimodal sensing signals obtained from multiple devices are fused for generating the deadlift behavior classifiers, 2) the recurrent neural network structure can analyze the information from the synchronized skeletal and inertial sensing data, and 3) a Vaplab dataset is generated for evaluating the deadlift behaviors recognizing capability in the proposed method.

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