Multiscale discriminant saliency for visual attention

Anh Cat Le Ngo, Kenneth Li Minn Ang, Guoping Qiu, Jasmine Seng Kah-Phooi

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review


The bottom-up saliency, an early stage of humans' visual attention, can be considered as a binary classification problem between center and surround classes. Discriminant power of features for the classification is measured as mutual information between features and two classes distribution. The estimated discrepancy of two feature classes very much depends on considered scale levels; then, multi-scale structure and discriminant power are integrated by employing discrete wavelet features and Hidden markov tree (HMT). With wavelet coefficients and Hidden Markov Tree parameters, quad-tree like label structures are constructed and utilized in maximum a posterior probability (MAP) of hidden class variables at corresponding dyadic sub-squares. Then, saliency value for each dyadic square at each scale level is computed with discriminant power principle and the MAP. Finally, across multiple scales is integrated the final saliency map by an information maximization rule. Both standard quantitative tools such as NSS, LCC, AUC and qualitative assessments are used for evaluating the proposed multiscale discriminant saliency method (MDIS) against the well-know information-based saliency method AIM on its Bruce Database wity eye-tracking data. Simulation results are presented and analyzed to verify the validity of MDIS as well as point out its disadvantages for further research direction.

Original languageEnglish
Title of host publicationComputational Science and Its Applications, ICCSA 2013 - 13th International Conference, Proceedings
PublisherSpringer Verlag
Number of pages21
EditionPART 1
ISBN (Print)9783642396366
Publication statusPublished - 2013
Externally publishedYes
Event13th International Conference on Computational Science and Its Applications, ICCSA 2013 - Ho Chi Minh City, Viet Nam
Duration: 24 Jun 201327 Jun 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7971 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference13th International Conference on Computational Science and Its Applications, ICCSA 2013
Country/TerritoryViet Nam
CityHo Chi Minh City


Dive into the research topics of 'Multiscale discriminant saliency for visual attention'. Together they form a unique fingerprint.

Cite this