Light Field Video Compression and Real Time Rendering

2019 ◽  
Vol 38 (7) ◽  
pp. 265-276
Author(s):  
Saghi Hajisharif ◽  
Ehsan Miandji ◽  
Per Larsson ◽  
Kiet Tran ◽  
Jonas Unger
Keyword(s):  
Real Time ◽  
Video Compression ◽  
Light Field

Spatial Interpolators for Intra-Frame Resampling of SAR Videos: A Comparative Study Using Real-Time HD, Medical and Radar Data

2020 ◽  
Vol 15 (2) ◽  
pp. 144-196 ◽  
Author(s):  
Mohammad R. Khosravi ◽  
Sadegh Samadi ◽  
Reza Mohseni
Keyword(s):  
Computational Complexity ◽  
Real Time ◽  
Video Compression ◽  
Nearest Neighbor ◽  
Radar Data ◽  
Edge Preservation ◽  
Edge Information ◽  
Video Codecs ◽  
Comparative Results ◽  
Interesting Area

Background: Real-time video coding is a very interesting area of research with extensive applications into remote sensing and medical imaging. Many research works and multimedia standards for this purpose have been developed. Some processing ideas in the area are focused on second-step (additional) compression of videos coded by existing standards like MPEG 4.14. Materials and Methods: In this article, an evaluation of some techniques with different complexity orders for video compression problem is performed. All compared techniques are based on interpolation algorithms in spatial domain. In details, the acquired data is according to four different interpolators in terms of computational complexity including fixed weights quartered interpolation (FWQI) technique, Nearest Neighbor (NN), Bi-Linear (BL) and Cubic Cnvolution (CC) interpolators. They are used for the compression of some HD color videos in real-time applications, real frames of video synthetic aperture radar (video SAR or ViSAR) and a high resolution medical sample. Results: Comparative results are also described for three different metrics including two reference- based Quality Assessment (QA) measures and an edge preservation factor to achieve a general perception of various dimensions of the mentioned problem. Conclusion: Comparisons show that there is a decidable trade-off among video codecs in terms of more similarity to a reference, preserving high frequency edge information and having low computational complexity.

Real-time multi-view background matting for 3D light field video

2021 ◽  
Author(s):  
Junfeng Chen ◽  
Xinzhu Sang ◽  
Jinhui Yuan ◽  
Binbin Yan ◽  
Duo Chen ◽  
...  
Keyword(s):  
Real Time ◽  
Light Field

Light field sensor and real-time panorama imaging multi-camera system and the design of data acquisition

2014 ◽  
Author(s):  
Yu Lu ◽  
Jiayuan Tao ◽  
Keyi Wang
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Light Field ◽  
Camera System ◽  
Field Sensor

scholarly journals A Compact Light Field Camera for Real-Time Depth Estimation

2019 ◽  
pp. 52-63 ◽  
Author(s):  
Yuriy Anisimov ◽  
Oliver Wasenmüller ◽  
Didier Stricker
Keyword(s):  
Real Time ◽  
Light Field ◽  
Depth Estimation

scholarly journals A crosstalk-suppressed dense multi-view light-field display based on real-time light-field pickup and reconstruction

2018 ◽  
Vol 26 (26) ◽  
pp. 34412 ◽  
Author(s):  
Le Yang ◽  
Xinzhu Sang ◽  
Xunbo Yu ◽  
Boyang Liu ◽  
Binbin Yan ◽  
...  
Keyword(s):  
Real Time ◽  
Light Field

OC-0508: 3D real-time water-equivalent dosimeter using a single light-field camera for pre-treatment QA

2014 ◽  
Vol 111 ◽  
pp. S200
Author(s):  
M. Goulet ◽  
M. Rilling ◽  
L. Gingras ◽  
S. Beddar ◽  
L. Beaulieu ◽  
...  
Keyword(s):  
Real Time ◽  
Light Field ◽  
Pre Treatment

The Challenges of Compressing and Streaming Real Time Video Originating from Mobile Devices

2012 ◽  
pp. 1-24
Author(s):  
Ngozi V. Uti ◽  
Richard Fox
Keyword(s):  
Real Time ◽  
Mobile Devices ◽  
Video Compression ◽  
Mobile Phones ◽  
Cell Phone ◽  
Academic Research ◽  
Streaming Video ◽  
The World ◽  
Computational Resources ◽  
Efficient Video

In recent years, mobile phones have become the de facto system of communication across the planet. Mobile phones have helped increase economic growth and critical response in many parts of the world. Mobile phones are even being used for data transmission. However, little academic research has been done on the specific problem of streaming real time video originating from the cameras of mobile devices over cell phone networks. There are many factors that complicate this problem including the limited computational resources of mobile phones, the low and variable bandwidth of cell phone networks, and the need for video compression and streaming algorithms that can be supported by both the mobile phones and cell phone networks. This chapter examines the problems involved and discusses on-going research on the topic. The main goal of this chapter is to identify the real time constraints and challenges of compressing and streaming video from mobile devices for the purpose of designing efficient video compression and streaming techniques that are able to work within the constraints of the limited computational resources and bandwidth available to mobile devices.

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