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Keypoint encoding and transmission for improved feature extraction from compressed images

Chao, Jianshu; Steinbach, Echehard; Xie, Lexing

Description

In many mobile visual analysis scenarios, compressed images are transmitted over a communication network for analysis at a server. Often, the processing at the server includes some form of feature extraction and matching. Image compression has been shown to have an adverse effect on feature matching performance. To address this issue, we propose to signal the feature keypoints as side information to the server, and extract only the feature descriptors from the compressed images. To this end, we...[Show more]

dc.contributor.authorChao, Jianshu
dc.contributor.authorSteinbach, Echehard
dc.contributor.authorXie, Lexing
dc.coverage.spatialTurin, Italy
dc.date.accessioned2016-06-14T23:20:28Z
dc.date.createdJune 29 - July 3 2015
dc.identifier.isbn9781479970827
dc.identifier.urihttp://hdl.handle.net/1885/103395
dc.description.abstractIn many mobile visual analysis scenarios, compressed images are transmitted over a communication network for analysis at a server. Often, the processing at the server includes some form of feature extraction and matching. Image compression has been shown to have an adverse effect on feature matching performance. To address this issue, we propose to signal the feature keypoints as side information to the server, and extract only the feature descriptors from the compressed images. To this end, we propose an approach to efficiently encode the locations, scales, and orientations of keypoints extracted from the original image. Furthermore, we propose a new approach for selecting relevant yet fragile keypoints as side information for the image, thus further reducing the data volume. We evaluate the performance of our approach using the Stanford mobile augmented reality dataset. Results show that the feature matching performance is significantly improved for images at low bitrate.
dc.publisherCurran Associates, Inc.
dc.relation.ispartofseriesIEEE International Conference on Multimedia and Expo, ICME 2015
dc.sourceProceedings - IEEE International Conference on Multimedia and Expo
dc.titleKeypoint encoding and transmission for improved feature extraction from compressed images
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2015
local.identifier.absfor080109 - Pattern Recognition and Data Mining
local.identifier.absfor080199 - Artificial Intelligence and Image Processing not elsewhere classified
local.identifier.absfor080611 - Information Systems Theory
local.identifier.ariespublicationU3488905xPUB6789
local.type.statusPublished Version
local.contributor.affiliationChao, Jianshu, Technische Universitat Munchen
local.contributor.affiliationSteinbach, Echehard, Technische Universitat Munchen
local.contributor.affiliationXie, Lexing, College of Engineering and Computer Science, ANU
local.description.embargo2037-12-31
local.bibliographicCitation.startpage1
local.bibliographicCitation.lastpage6
local.identifier.doi10.1109/ICME.2015.7177388
local.identifier.absseo970108 - Expanding Knowledge in the Information and Computing Sciences
dc.date.updated2016-06-14T08:49:24Z
local.identifier.scopusID2-s2.0-84946093742
CollectionsANU Research Publications

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