Online dictionary learning on symmetric positive definite manifolds with vision applications

Shengping Zhang, Shiva Kasiviswanathan, Pong C. Yuen, Mehrtash Harandi

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

35 Citations (Scopus)


Symmetric Positive Definite (SPD) matrices in the form of region covariances are considered rich descriptors for images and videos. Recent studies suggest that exploiting the Riemannian geometry of the SPD manifolds could lead to improved performances for vision applications. For tasks involving processing large-scale and dynamic data in computer vision, the underlying model is required to progressively and efficiently adapt itself to the new and unseen observations. Motivated by these requirements, this paper studies the problem of online dictionary learning on the SPD manifolds. We make use of the Stein divergence to recast the problem of online dictionary learning on the manifolds to a problem in Reproducing Kernel Hilbert Spaces, for which, we develop efficient algorithms by taking into account the geometric structure of the SPD manifolds. To our best knowledge, our work is the first study that provides a solution for online dictionary learning on the SPD manifolds. Empirical results on both large-scale image classification task and dynamic video processing tasks validate the superior performance of our approach as compared to several state-of-the-art algorithms.

Original languageEnglish
Title of host publicationProceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence
EditorsBlai Bonet, Sven Koenig
Place of PublicationPalo Alto CA USA
PublisherAssociation for the Advancement of Artificial Intelligence (AAAI)
Number of pages9
ISBN (Print)9781577357025
Publication statusPublished - 1 Jun 2015
Externally publishedYes
EventAAAI Conference on Artificial Intelligence 2015 - Hyatt Regency, Austin, United States of America
Duration: 25 Jan 201530 Jan 2015
Conference number: 29th


ConferenceAAAI Conference on Artificial Intelligence 2015
Abbreviated titleAAAI 2015
CountryUnited States of America
OtherCo-located with the 27th Innovative Applications of Artificial Intelligence Conference. Papers at the AAAI 2015 conference will be related here. Any papers presented at the IAAI 2015 part of the conference will be related to that event. The two conferences should have a "relation" to each other put in place to recognise that the conferences were combined into one proceedings.
Internet address

Cite this