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Shonali Balakrishna

dblp:188/1210 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%
Computer graphics and multimedia
1 paper
Virtual and augmented reality · 77% Visualization and visual analytics · 23%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval
image retrieval
0.212016
Exploration of Large Image Corpuses in Virtual Reality · ACM Multimedia 2016
Information retrieval
interactive information retrieval
0.212016
Exploration of Large Image Corpuses in Virtual Reality · ACM Multimedia 2016
Virtual and augmented reality
immersive interaction
0.212016
Exploration of Large Image Corpuses in Virtual Reality · ACM Multimedia 2016
Visualization and visual analytics
graph-based navigation
0.112016
Exploration of Large Image Corpuses in Virtual Reality · ACM Multimedia 2016
YearPublicationVenuePosition
2016 Exploration of Large Image Corpuses in Virtual Reality
abstract
With the increasing capture of photos and their proliferation on social media, there is a pressing need for a more intuitive and versatile image search and exploration system. Image search systems have long been confined to the binds of the 2D legacy screens and the keyword text-box. With the recent advances in Virtual Reality (VR) technology, a move towards an immersive VR environment will redefine the image navigation experience. To this end, we propose a VR platform that gathers images from various sources, and addresses the 5 Ws of image search - what, where, when, who and why. We achieve this by providing the user with two modes of interactive exploration - (i) A mode that allows for a graph based navigation of an image dataset, using a steering wheel visualization, along multiple dimensions of time, location, visual concept, people, etc. and (ii) Another mode that provides an intuitive exploration of the image dataset using a logical hierarchy of visual concepts. Our contributions include creating a VR image exploration experience that is intuitive and allows image navigation along multiple dimensions.
Sanket Khanwalkar, Shonali Balakrishna, Ramesh Jain 0001
ACM Multimedia2