Natural exploration of 3D massive models on large-scale light field displays using the FOX proximal navigation technique

2012 ◽  
Vol 36 (8) ◽  
pp. 893-903 ◽  
Author(s):  
Fabio Marton ◽  
Marco Agus ◽  
Enrico Gobbetti ◽  
Giovanni Pintore ◽  
Marcos Balsa Rodriguez
Keyword(s):  
Large Scale ◽  
Light Field ◽  
Massive Models

scholarly journals Large-Scale Light Field Capture and Reconstruction

2020 ◽  
Author(s):  
Yuan Gao
Keyword(s):  
Coordinate System ◽  
Real World ◽  
Large Scale ◽  
Light Field ◽  
Geometric Constraints ◽  
Video Frame ◽  
Coordinate Frame ◽  
Light Fields ◽  
Synthesis Methods ◽  
Kinect V2

This thesis discusses approaches and techniques to convert Sparsely- Sampled Light Fields (SSLFs) into Densely-Sampled Light Fields (DSLFs), which can be used for visualization on 3DTV and Virtual Reality (VR) de- vices. Exemplarily, a movable 1D large-scale light field acquisition system for capturing SSLFs in real-world environments is evaluated. This system consists of 24 sparsely placed RGB cameras and two Kinect V2 sensors. The real-world SSLF data captured with this setup can be leveraged to reconstruct real-world DSLFs. To this end, three challenging problems require to be solved for this system: (i) how to estimate the rigid trans- formation from the coordinate system of a Kinect V2 to the coordinate system of an RGB camera; (ii) how to register the two Kinect V2 sensors with a large displacement; (iii) how to reconstruct a DSLF from a SSLF with moderate and large disparity ranges. To overcome these three challenges, we propose: (i) a novel self- calibration method, which takes advantage of the geometric constraints from the scene and the cameras, for estimating the rigid transformations from the camera coordinate frame of one Kinect V2 to the camera coordi- nate frames of 12-nearest RGB cameras; (ii) a novel coarse-to-fine approach for recovering the rigid transformation from the coordinate system of one Kinect to the coordinate system of the other by means of local color and geometry information; (iii) several novel algorithms that can be categorized into two groups for reconstructing a DSLF from an input SSLF, including novel view synthesis methods, which are inspired by the state-of-the-art video frame interpolation algorithms, and Epipolar-Plane Image (EPI) in- painting methods, which are inspired by the Shearlet Transform (ST)-based DSLF reconstruction approaches.

scholarly journals Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs

2021 ◽  
Vol 9 ◽  
pp. 978-994
Author(s):  
Emanuele Bugliarello ◽  
Ryan Cotterell ◽  
Naoaki Okazaki ◽  
Desmond Elliott
Keyword(s):  
Language Processing ◽  
Large Scale ◽  
Meta Analysis ◽  
Training Data ◽  
Fine Tuning ◽  
Controlled Experiments ◽  
Unified Framework ◽  
Massive Models ◽  
Vision And Language ◽  
And Task

Abstract Large-scale pretraining and task-specific fine- tuning is now the standard methodology for many tasks in computer vision and natural language processing. Recently, a multitude of methods have been proposed for pretraining vision and language BERTs to tackle challenges at the intersection of these two key areas of AI. These models can be categorized into either single-stream or dual-stream encoders. We study the differences between these two categories, and show how they can be unified under a single theoretical framework. We then conduct controlled experiments to discern the empirical differences between five vision and language BERTs. Our experiments show that training data and hyperparameters are responsible for most of the differences between the reported results, but they also reveal that the embedding layer plays a crucial role in these massive models.

A large-scale multi-projection light-field display based on multi-view sampling calibration

2018 ◽  
Vol 47 (6) ◽  
pp. 603004
Author(s):  
倪丽霞 Ni Lixia ◽  
李海峰 Li Haifeng ◽  
刘 旭 Liu Xu
Keyword(s):  
Large Scale ◽  
Light Field

scholarly journals High-speed large-scale 4D activities mapping of moving C. elegans by deep-learning-enabled light-field microscopy on a chip

2021 ◽  
Author(s):  
Tingting Zhu ◽  
Lanxin Zhu ◽  
Yi Li ◽  
Xiaopeng Chen ◽  
Mingyang He ◽  
...  
Keyword(s):  
Deep Learning ◽  
High Speed ◽  
Large Scale ◽  
Light Field ◽  
Wild Type ◽  
C Elegans ◽  
Neural Activities ◽  
Biological Studies ◽  
Different Types ◽  
Field Imaging

We report a novel fusion of microfluidics and light-field microscopy, to achieve high-speed 4D (space + time) imaging of moving C. elegans on a chip. Our approach combines automatic chip-based worm loading / compartmentalization / flushing / reloading with instantaneous deep-learning light-field imaging of moving worm. Taken together, we realized intoto image-based screening of wild-type and uncoordinated-type worms at a volume rate of 33 Hz, with sustained observation of 1 minute per worm, and overall throughput of 42 worms per hour. With quickly yielding over 80000 image volumes that four-dimensionally visualize the dynamics of all the worms, we can quantitatively analyse their behaviours as well as the neural activities, and correlate the phenotypes with the neuron functions. The different types of worms can be readily identified as a result of the high-throughput activity mapping. Our approach shows great potential for various lab-on-a-chip biological studies, such as embryo sorting and cell growth assays.

360-degree large-scale multiprojection light-field 3D display system

2018 ◽  
Vol 57 (8) ◽  
pp. 1817 ◽  
Author(s):  
Lixia Ni ◽  
Zhenxing Li ◽  
Haifeng Li ◽  
Xu Liu
Keyword(s):  
Large Scale ◽  
Light Field ◽  
Display System ◽  
3D Display

Cinema as large as life: Large-scale light field cinema system

2017 ◽  
Author(s):  
Peter A. Kara ◽  
Maria G. Martini ◽  
Zsolt Nagy ◽  
Attila Barsi
Keyword(s):  
Large Scale ◽  
Light Field

7-3: A Large-scale Multi-projection Light-field Display based on Multi-view Sampling Calibration

2018 ◽  
Vol 49 (1) ◽  
pp. 68-71
Author(s):  
Lixia Ni ◽  
Zhenxing Li ◽  
Haifeng Li ◽  
Rui Wang ◽  
Xu Liu
Keyword(s):  
Large Scale ◽  
Light Field

scholarly journals View-dependent exploration of massive volumetric models on large-scale light field displays

2010 ◽  
Vol 26 (6-8) ◽  
pp. 1037-1047 ◽  
Author(s):  
José Antonio Iglesias Guitián ◽  
Enrico Gobbetti ◽  
Fabio Marton
Keyword(s):  
Large Scale ◽  
Light Field ◽  
Volumetric Models
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