short-paper

Interactive visual object search through mutual information maximization

Authors:

Ying WuAuthors Info & Claims

MM '10: Proceedings of the 18th ACM international conference on Multimedia

Pages 1147 - 1150

https://doi.org/10.1145/1873951.1874172

Published: 25 October 2010 Publication History

Get Access

Abstract

Searching for small objects (e.g., logos) in images is a critical yet challenging problem. It becomes more difficult when target objects differ significantly from the query object due to changes in scale, viewpoint or style, not to mention partial occlusion or cluttered backgrounds. With the goal to retrieve and accurately locate the small object in the images, we formulate the object search as the problem of finding subimages with the largest mutual information toward the query object. Each image is characterized by a collection of local features. Instead of only using the query object for matching, we propose a discriminative matching using both positive and negative queries to obtain the mutual information score. The user can verify the retrieved subimages and improve the search results incrementally. Our experiments on a challenging logo database of 10,000 images highlight the effectiveness of this approach.

References

[1]

Christoph H. Lampert,Detecting objects in large image collections and videos by efficient subimage retrieval, Proc. IEEE Intl. Conf. on Computer Vision, 2009.

Crossref

Google Scholar

[2]

Saloua Litayem, Alexis Joly, and Nozha Boujemaa, Interactive object retrieval with efficient boosting, ACM Multimedia, 2009.

Digital Library

Google Scholar

[3]

Jim Kleban, Xing Xie, and Wei-Ying Ma, Spatial pyramid mining for logo detection in natural scenes, Proc. IEEE Conf. on Multimedia Expo, 2008, pp. 1077--1080.

Crossref

Google Scholar

[4]

Alexis Joly nd Olivier Buisson, Logo retrieval with a contrario visual query expansion,Proc. ACM Multimedia, 2009.

Digital Library

Google Scholar

[5]

Josef Sivic and Andrew Zisserman, Video google: A text retrieval approach to object matching in videos, Proc. IEEE Intl. Conf. on Computer Vision, 2003.

Digital Library

Google Scholar

[6]

David Lowe,Distinctive image features from scale-invariant keypoints,Intl. Journal of Computer Vision, 2004.

Digital Library

Google Scholar

[7]

Junsong Yuan, Zicheng Liu, and Ying Wu, Discriminative subvolume search for efficient action detection, Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 2009.

Google Scholar

[8]

O. Boiman, E. Shechtman, and M. Irani,In defense of nearest-neighbor based image classification,in Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 2008.

Crossref

Google Scholar

[9]

Mayur Datar, Nicole Immorlica, Piotr Indyk, and Vahab Mirrokni,Locality-sensitive hashing scheme based on p-stable distribution,in Proc. of Twentieth Annual Symposium on Computational Geometry, 2004, pp. 253--262.

Digital Library

Google Scholar

[10]

Christoph H. Lampert, Matthew B. Blaschko, and Thomas Hofmann,Beyond sliding windows: Object localization by efficient subwindow search,in Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 2008.

Google Scholar

[11]

K. Mikolajczyk and C. Schmid,A performance evaluation of local descriptors,IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 27, no. 10, pp. 1615--1630,2005.

Digital Library

Google Scholar

Cited By

View all

Balamurugan GArulalan VPremanand V(2023)Object Detection Using a YOLOv4 Model in Video Surveillance2023 4th International Conference on Smart Electronics and Communication (ICOSEC)10.1109/ICOSEC58147.2023.10275864(9-14)Online publication date: 20-Sep-2023
https://doi.org/10.1109/ICOSEC58147.2023.10275864
Lu CLi DZeng D(2019)Logo Detection Based on Convolutional Neural Networks2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)10.1109/ICSIDP47821.2019.9173284(1-6)Online publication date: Dec-2019
https://doi.org/10.1109/ICSIDP47821.2019.9173284
Yu TWu YBhattacharjee SYuan JSingh SMarkovitch S(2017)Efficient object instance search using fuzzy objects matchingProceedings of the Thirty-First AAAI Conference on Artificial Intelligence10.5555/3298023.3298194(4320-4326)Online publication date: 4-Feb-2017
https://dl.acm.org/doi/10.5555/3298023.3298194
Show More Cited By

Index Terms

Interactive visual object search through mutual information maximization
1. Information systems
  1. Information retrieval
    1. Retrieval models and ranking

Recommendations

Alignment by maximization of mutual information
ICCV '95: Proceedings of the Fifth International Conference on Computer Vision

A new information-theoretic approach is presented for finding the pose of an object in an image. The technique does not require information about the surface properties of the object, besides its shape, and is robust with respect to variations of ...
Graph matching vs mutual information maximization for object detection
Query Adaptive Instance Search using Object Sketches
MM '16: Proceedings of the 24th ACM international conference on Multimedia

Sketch-based object search is a challenging problem mainly due to two difficulties: (1) how to match the binary sketch query with the colorful image, and (2) how to locate the small object in a big image with the sketch query. To address the above ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

MM '10: Proceedings of the 18th ACM international conference on Multimedia

October 2010

1836 pages

ISBN:9781605589336

DOI:10.1145/1873951

General Chairs:
Alberto del Bimbo
University of Florence, Italy
,
Shih-Fu Chang
Columbia University, USA
,
Program Chair:
Arnold Smeulders
University of Amsterdam, NL

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 October 2010

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Short-paper

Conference

MM '10

Sponsor:

SIGMM

MM '10: ACM Multimedia Conference

October 25 - 29, 2010

Firenze, Italy

Acceptance Rates

Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

20
Total Citations
View Citations
187
Total Downloads

Downloads (Last 12 months)4
Downloads (Last 6 weeks)1

Reflects downloads up to 12 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Balamurugan GArulalan VPremanand V(2023)Object Detection Using a YOLOv4 Model in Video Surveillance2023 4th International Conference on Smart Electronics and Communication (ICOSEC)10.1109/ICOSEC58147.2023.10275864(9-14)Online publication date: 20-Sep-2023
https://doi.org/10.1109/ICOSEC58147.2023.10275864
Lu CLi DZeng D(2019)Logo Detection Based on Convolutional Neural Networks2019 IEEE International Conference on Signal, Information and Data Processing (ICSIDP)10.1109/ICSIDP47821.2019.9173284(1-6)Online publication date: Dec-2019
https://doi.org/10.1109/ICSIDP47821.2019.9173284
Yu TWu YBhattacharjee SYuan JSingh SMarkovitch S(2017)Efficient object instance search using fuzzy objects matchingProceedings of the Thirty-First AAAI Conference on Artificial Intelligence10.5555/3298023.3298194(4320-4326)Online publication date: 4-Feb-2017
https://dl.acm.org/doi/10.5555/3298023.3298194
Bhattacharjee SYuan JTan YDuan L(2016)Query-Adaptive Small Object Search Using Object Proposals and Shape-Aware DescriptorsIEEE Transactions on Multimedia10.1109/TMM.2016.253260118:4(726-737)Online publication date: Apr-2016
https://doi.org/10.1109/TMM.2016.2532601
Meng JYuan JYang JWang GTan Y(2016)Object Instance Search in Videos via Spatio-Temporal Trajectory DiscoveryIEEE Transactions on Multimedia10.1109/TMM.2015.250073418:1(116-127)Online publication date: Jan-2016
https://doi.org/10.1109/TMM.2015.2500734
(2016)On interactive learning-to-rank for IRNeurocomputing10.1016/j.neucom.2016.03.084208:C(3-24)Online publication date: 5-Oct-2016
https://dl.acm.org/doi/10.1016/j.neucom.2016.03.084
Das Bhattacharjee SYuan JTan YDuan LZhou XSmeaton ATian QBulterman DShen HMayer-Patel KYan S(2015)Query-Adaptive Logo Search using Shape-Aware DescriptorsProceedings of the 23rd ACM international conference on Multimedia10.1145/2733373.2806305(1155-1158)Online publication date: 13-Oct-2015
https://dl.acm.org/doi/10.1145/2733373.2806305
Yuning Jiang Jingjing Meng Junsong Yuan Jiebo Luo (2015)Randomized Spatial Context for Object SearchIEEE Transactions on Image Processing10.1109/TIP.2015.240533724:6(1748-1762)Online publication date: Jun-2015
https://doi.org/10.1109/TIP.2015.2405337
Kesidis AKaratzas D(2014)Logo and Trademark RecognitionHandbook of Document Image Processing and Recognition10.1007/978-0-85729-859-1_16(591-646)Online publication date: 30-Apr-2014
https://doi.org/10.1007/978-0-85729-859-1_16
Meng JYuan JGang Wang Jianbo Xu (2013)Object instance search in videos2013 9th International Conference on Information, Communications & Signal Processing10.1109/ICICS.2013.6782862(1-4)Online publication date: Dec-2013
https://doi.org/10.1109/ICICS.2013.6782862
Show More Cited By

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

Alignment by maximization of mutual information

Graph matching vs mutual information maximization for object detection

Query Adaptive Instance Search using Object Sketches