NDLI: Widening siamese architectures for stereo matching

Please wait, while we are loading the content...

Widening siamese architectures for stereo matching

Content Provider	Scilit
Author	Brandao, Patrick Mazomenos, Evangelos Stoyanov, Danail
Copyright Year	2018
Description	Journal: Pattern Recognition Letters Computational stereo is one of the classical problems in computer vision. Numerous algorithms and solutions have been reported in recent years focusing on developing methods for computing similarity, aggregating it to obtain spatial support and finally optimizing an energy function to find the final disparity. In this paper, we focus on the feature extraction component of stereo matching architecture and we show standard CNNs operation can be used to improve the quality of the features used to find point correspondences. Furthermore, we use a simple space aggregation that hugely simplifies the correlation learning problem, allowing us to better evaluate the quality of the features extracted. Our results on benchmark data are compelling and show promising potential even without refining the solution.
Related Links	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6472548/pdf
Ending Page	81
Page Count	7
Starting Page	75
ISSN	01678655
DOI	10.1016/j.patrec.2018.12.002
Journal	Pattern Recognition Letters
Volume Number	120
Language	English
Publisher	Elsevier BV
Publisher Date	2019-04-01
Access Restriction	Open
Subject Keyword	Journal: Pattern Recognition Letters Information Systems Stereo Matching Convolutional Neural Network Computer Vision
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Signal Processing Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Text-independent writer identification using convolutional neural network

Using filter banks in Convolutional Neural Networks for texture classification

Widening siamese architectures for stereo matching

Order-aware convolutional pooling for video based action recognition

Depth-based subgraph convolutional auto-encoder for network representation learning

Local Deep Neural Networks for gender recognition

Video semantic object segmentation by self-adaptation of DCNN

Quantum-based subgraph convolutional neural networks

Optimized projection for hashing

Widening siamese architectures for stereo matching

Similar Documents

Text-independent writer identification using convolutional neural network

Using filter banks in Convolutional Neural Networks for texture classification

Widening siamese architectures for stereo matching

Order-aware convolutional pooling for video based action recognition

Depth-based subgraph convolutional auto-encoder for network representation learning

Local Deep Neural Networks for gender recognition

Video semantic object segmentation by self-adaptation of DCNN

Quantum-based subgraph convolutional neural networks

Optimized projection for hashing

Widening siamese architectures for stereo matching