Proceedings ArticleDOI
A Rich Stereoscopic 3D High Dynamic Range Image & Video Database of Natural Scenes
Aditya Wadaskar,Mansi Sharma,Rohan Lal +2 more
- pp 1-8
Reads0
Chats0
TLDR
This work proposes to make publicly available to the research community, a diversified database of Stereoscopic 3D HDR images and videos, captured within the beautiful campus of Indian Institute of Technology, Madras, which is blessed with rich flora and fauna, and is home to several rare wildlife species.Abstract:
The consumer market of High Dynamic Range (HDR) displays and cameras is blooming rapidly with the advent of 3D video and display technologies. Specialised agencies like Moving Picture Experts Group and International Telecommunication Union are demanding the standardization of latest display advancements. Lack of sufficient experimental data is a major bottleneck for the development of preliminary research efforts in 3D HDR video technology. We propose to make publicly available to the research community, a diversified database of Stereoscopic 3D HDR images and videos, captured within the beautiful campus of Indian Institute of Technology, Madras, which is blessed with rich flora and fauna, and is home to several rare wildlife species. Further, we have described the procedure of capturing, aligning, calibrating and post-processing of 3D images and videos. We have discussed research opportunities and challenges, and the potential use cases of HDR stereo 3D applications and depth-from-HDR aspects.read more
Citations
More filters
Journal ArticleDOI
MEStereo-Du2CNN: A Novel Dual Channel CNN for Learning Robust Depth Estimates from Multi-exposure Stereo Images for HDR 3D Applications
TL;DR: In this article , a dual-encoder single-decoder CNN with different weights for feature fusion is proposed for depth estimation of multi-exposure stereo image sequences in 3D HDR video content.
Journal ArticleDOI
2T-UNET: A Two-Tower UNet with Depth Clues for Robust Stereo Depth Estimation
TL;DR: The depth estimation problem is revisits, avoiding the explicit stereo matching step using a simple two-tower convolutional neural network, and the proposed algorithm is entitled 2T-UNet, which surpasses state-of-the-art monocular and stereo depth estimation methods on the challenging Scene dataset.
Journal ArticleDOI
A High Resolution Multi-exposure Stereoscopic Image & Video Database of Natural Scenes
TL;DR: A diversified stereoscopic multi-exposure dataset captured within the campus of Indian Institute of Technology Madras, which is home to a diverse fauna and fauna is introduced and accommodates wide depth range, complex depth structure, complicate object movement, illumination variations, rich color dynamics, texture discrepancy.
References
More filters
Proceedings ArticleDOI
Secrets of optical flow estimation and their principles
TL;DR: It is discovered that “classical” flow formulations perform surprisingly well when combined with modern optimization and implementation techniques, and while median filtering of intermediate flow fields during optimization is a key to recent performance gains, it leads to higher energy solutions.
Proceedings ArticleDOI
A region based stereo matching algorithm using cooperative optimization
Zengfu Wang,Zhigang Zheng +1 more
TL;DR: The proposed algorithm uses regions as matching primitives and defines the corresponding region energy functional for matching by utilizing the color statistics of regions and the constraints on smoothness and occlusion between adjacent regions.
Proceedings Article
Depth estimation using monocular and stereo cues
TL;DR: This paper shows that by adding monocular cues to stereo (triangulation) ones, it is shown that significantly more accurate depth estimates are obtained than is possible using either monocular or stereo cues alone.
Proceedings Article
DPSNet: End-to-end Deep Plane Sweep Stereo
TL;DR: A convolutional neural network called DPSNet (Deep Plane Sweep Network) whose design is inspired by best practices of traditional geometry-based approaches for dense depth reconstruction, achieves state-of-the-art reconstruction results on a variety of challenging datasets.
Journal ArticleDOI
Three-Dimensional Video Postproduction and Processing
Aljosa Smolic,Peter Kauff,Sebastian Knorr,Alexander Hornung,M Kunter,Marcus Müller,Manuel Lang +6 more
TL;DR: This paper gives an overview of the state-of-the-art in 3-D video postproduction and processing as well as an outlook to remaining challenges and opportunities.
Related Papers (5)
Content-based scene detection and analysis method for automatic classification of TV sports news
Kazimierz Choroś,Piotr Pawlaczyk +1 more