Video Stabilization of the NAO Robot Using IMU Data

2019 ◽  
pp. 147-162
Author(s):  
Oswualdo Alquisiris-Quecha ◽  
Jose Martinez-Carranza
Keyword(s):  
Video Stabilization ◽  
Nao Robot

Image Stitching Algorithms - A Review

2016 ◽  
Vol 1 (2) ◽  
pp. 14-18
Author(s):  
Srishty Suman ◽  
Utkarsh Rastogi ◽  
Rajat Tiwari
Keyword(s):  
Video Compression ◽  
Video Summarization ◽  
Video Stabilization ◽  
Image Stitching

Image stitching is the process of combining two or more images of the same scene as a single larger image. Image stitching is needed in many applications like video stabilization, video summarization, video compression, panorama creation. The effectiveness of image stitching depends on the overlap removal, matching of the intensity of images, the techniques used for blending the image. In this paper, the various techniques devised earlier for the image stitching and their applications in the relative places has been reviewed.

A Three-Site Reproduction of the Joint Simon Effect with the NAO Robot

2020 ◽  
Author(s):  
Megan Strait ◽  
Florian Lier ◽  
Jasmin Bernotat ◽  
Sven Wachsmuth ◽  
Friederike Eyssel ◽  
...  
Keyword(s):  
Simon Effect ◽  
Nao Robot

scholarly journals Cinematic-L1 Video Stabilization with a Log-Homography Model

2021 ◽  
Author(s):  
Arwen Bradley ◽  
Jason Klivington ◽  
Joseph Triscari ◽  
Rudolph van der Merwe
Keyword(s):  
Video Stabilization

Self-Localization in Highly Dynamic Environments Based on Dual-Channel Unscented Particle Filter

Robotica ◽  
2020 ◽  
pp. 1-14
Author(s):  
Chen Hao ◽  
Liu Chengju ◽  
Chen Qijun
Keyword(s):  
Particle Filter ◽  
Humanoid Robots ◽  
Dynamic Environments ◽  
Measurement Unit ◽  
Dual Channel ◽  
Nao Robot ◽  
Unscented Particle Filter ◽  
Monte Carlo Localization ◽  
Switch Mechanism ◽  
Updating Procedure

SUMMARY Self-localization in highly dynamic environments is still a challenging problem for humanoid robots with limited computation resource. In this paper, we propose a dual-channel unscented particle filter (DC-UPF)-based localization method to address it. A key novelty of this approach is that it employs a dual-channel switch mechanism in measurement updating procedure of particle filter, solving for sparse vision feature in motion, and it leverages data from a camera, a walking odometer, and an inertial measurement unit. Extensive experiments with an NAO robot demonstrate that DC-UPF outperforms UPF and Monte–Carlo localization with regard to accuracy.

scholarly journals Mechanical and Electronic Video Stabilization Strategy of Mortars with Trajectory Correction Fuze Based on Infrared Image Sensor

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2461 ◽  
Author(s):  
Cong Zhang ◽  
Dongguang Li
Keyword(s):  
Motion Vector ◽  
Computational Cost ◽  
Infrared Image ◽  
Image Sensor ◽  
Projection Algorithm ◽  
Video Stabilization ◽  
Sensors And Actuators ◽  
Simulation And Experiment ◽  
Transformation Relation ◽  
Trajectory Correction

For a higher attack accuracy of projectiles, a novel mechanical and electronic video stabilization strategy is proposed for trajectory correction fuze. In this design, the complexity of sensors and actuators were reduced. To cope with complex combat environments, an infrared image sensor was used to provide video output. Following the introduction of the fuze’s workflow, the limitation of sensors for mechanical video stabilization on fuze was proposed. Particularly, the parameters of the infrared image sensor that strapdown with fuze were calculated. Then, the transformation relation between the projectile’s motion and the shaky video was investigated so that the electronic video stabilization method could be determined. Correspondingly, a novel method of dividing sub-blocks by adaptive global gray threshold was proposed for the image pre-processing. In addition, the gray projection algorithm was used to estimate the global motion vector by calculating the correlation between the curves of the adjacent frames. An example simulation and experiment were implemented to verify the effectiveness of this strategy. The results illustrated that the proposed algorithm significantly reduced the computational cost without affecting the accuracy of the motion estimation. This research provides theoretical and experimental basis for the intelligent application of sensor systems on fuze.

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