NDLI: Ego-Motion Estimation on Range Images Using High-Order Polynomial Expansion

Content Provider	IEEE Xplore Digital Library
Author	Okorn, B. Harguess, J.
Copyright Year	2014
Description	Author affiliation: Space & Naval Warfare Syst. Center Pacific, San Diego, CA, USA (Okorn, B.; Harguess, J.)
Abstract	This paper presents two novel algorithms for estimating the (local and global) motion in a series of range images based on a polynomial expansion. The use of polynomial expansion has been quite successful in estimating optical flow in 2D imagery, but has not been used extensively in 3D or range imagery. In both methods, each range image is approximated by applying a high-order polynomial expansion to local neighborhoods within the range image. In the local motion algorithm, these approximations are then used to derive the translation or displacement estimation within the local neighborhoods from frame to frame within the series of range images (also known as range image flow). An iterative method for computing the local translations is presented. In the global motion algorithm, a global motion model framework is utilized to compute a global motion estimation based on the polynomial expansion of the range images. We evaluate the algorithms on several real-world range image sequences with promising results.
Sponsorship	IEEE Comput. Soc.
Starting Page	299
Ending Page	306
File Size	1019828
Page Count	8
File Format	PDF
ISBN	9781479943081
ISSN	21607516
DOI	10.1109/CVPRW.2014.53
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Motion estimation Range Image Flow Estimation Range Image Optical imaging Visual Odometry Polynomials Mathematical model Optical sensors Robotics Range Image Odometry Optical Flow
Content Type	Text
Resource Type	Article

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

Leveraging Deep Learning for Visual Odometry Using Optical Flow

Ego-Motion Estimation Using Recurrent Convolutional Neural Networks through Optical Flow Learning

Visual odometry using commodity optical flow (2004)

Visual odometry using optic flow for Unmanned Aerial Vehicles

Visual Odometry for Velocity Estimation of UGVs

Visual odometry using commodity optical flow (2004)

Visual odometry using commodity optical flow (2004)

Model-based ego-motion and vehicle parameter estimation using visual odometry

A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera

Ego-Motion Estimation on Range Images Using High-Order Polynomial Expansion

Similar Documents

Leveraging Deep Learning for Visual Odometry Using Optical Flow

Ego-Motion Estimation Using Recurrent Convolutional Neural Networks through Optical Flow Learning

Visual odometry using commodity optical flow (2004)

Visual odometry using optic flow for Unmanned Aerial Vehicles

Visual Odometry for Velocity Estimation of UGVs

Visual odometry using commodity optical flow (2004)

Visual odometry using commodity optical flow (2004)

Model-based ego-motion and vehicle parameter estimation using visual odometry

A Robust Method for Ego-Motion Estimation in Urban Environment Using Stereo Camera

Ego-Motion Estimation on Range Images Using High-Order Polynomial Expansion