NDLI: Depth Error Elimination for RGB-D Cameras

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ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 8

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 7

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Visual Understanding with RGB-D Sensors: An Introduction to the Special Issue

Kinect Depth Recovery Using a Color-Guided, Region-Adaptive, and Depth-Selective Framework

Depth Error Elimination for RGB-D Cameras

A Combined Approach Toward Consistent Reconstructions of Indoor Spaces Based on 6D RGB-D Odometry and KinectFusion

Robust Multiview Feature Learning for RGB-D Image Understanding

From RGB-D Images to RGB Images: Single Labeling for Mining Visual Models

Accurate and Robust Moving-Object Segmentation for Telepresence Systems

Fusing Multiple Features for Depth-Based Action Recognition

An Evaluation of Gamesourced Data for Human Pose Estimation

Latent Support Vector Machine Modeling for Sign Language Recognition with Kinect

A Real-Time Hand Posture Recognition System Using Deep Neural Networks

Real-Time System for Driver Fatigue Detection by RGB-D Camera

An Approach to Ballet Dance Training through MS Kinect and Visualization in a CAVE Virtual Reality Environment

Exploring Spatial Correlation for Visual Object Retrieval

Pattern Matching Techniques for Replacing Missing Sections of Audio Streamed across Wireless Networks

An Association-Based Unified Framework for Mining Features and Opinion Words

A Hybrid Multigroup Coclustering Recommendation Framework Based on Information Fusion

Data Mining of Online Genealogy Datasets for Revealing Lifespan Patterns in Human Population

Issue 1, April 2015

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 5

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 4

ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 3

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ACM Transactions on Intelligent Systems and Technology (TIST) : Volume 1

Depth Error Elimination for RGB-D Cameras

Content Provider	ACM Digital Library
Author	Yang, You Gao, Yue Zhen, Yi Dai, Qionghai
Copyright Year	2015
Abstract	The rapid spreading of RGB-D cameras has led to wide applications of 3D videos in both academia and industry, such as 3D entertainment and 3D visual understanding. Under these circumstances, extensive research efforts have been dedicated to RGB-D camera--oriented topics. In these topics, quality promotion of depth videos with the temporal characteristic is emerging and important. Due to the limited exposure time of RGB-D cameras, object movement can easily lead to motion blurs in intensive images, which can further result in obvious artifacts (holes or fake boundaries) in the corresponding depth frames. With regard to this problem, we propose a depth error elimination method based on time series analysis to remove the artifacts in depth images. In this method, we first locate the regions with erroneous depths in intensive images by using motion blur detection based on a time series analysis model. This is based on the fact that the depth image is calculated by intensive color images that are captured synchronously by RGB-D cameras. Then, the artifacts, such as holes or fake boundaries, are fixed by a depth error elimination method. To evaluate the performance of the proposed method, we conducted experiments on 250 images. Experimental results demonstrate that the proposed method can locate the error regions correctly and eliminate these artifacts effectively. The quality of depth video can be improved significantly by using the proposed method.
Starting Page	1
Ending Page	16
Page Count	16
File Format	PDF
ISSN	21576904
e-ISSN	21576912
DOI	10.1145/2735959
Volume Number	6
Issue Number	2
Journal	ACM Transactions on Intelligent Systems and Technology (TIST)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-04-22
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Depth error RGB-D cameras Depth video Time series analysis
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Theoretical Computer Science

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

Real-Time System for Driver Fatigue Detection by RGB-D Camera

Robust Multiview Feature Learning for RGB-D Image Understanding

High-Quality Depth Map Upsampling and Completion for RGB-D Cameras

Structure Selective Depth Superresolution for RGB-D Cameras.

DART: dense articulated real-time tracking with consumer depth cameras

Fusing Multiple Features for Depth-Based Action Recognition

From RGB-D Images to RGB Images: Single Labeling for Mining Visual Models

Visual Understanding with RGB-D Sensors: An Introduction to the Special Issue

A real-time method for depth enhanced visual odometry

Depth Error Elimination for RGB-D Cameras

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