Events Calendar

PhD Defense - Abdullah Alfarrarjeh

PhD Candidate: Abdullah Alfarrarjeh

Committee:
Cyrus Shahabi (chair)
Aiichiro Nakano
C.-C. Jay Kuo

Location: PHE 325

Time: October 23rd, 10 am.

Title: Enabling Spatial-Visual Search for Geospatial Image Databases

Abstract:
Due to continuous advances in camera technologies as well as camera-enabled devices (e.g., CCTV, smartphone, vehicle blackbox, and GoPro), urban streets have been documented by massive amounts of images. Moreover, nowadays, images are typically tagged with spatial metadata due to various sensors (e.g., GPS and digital compass) attached to or embedded in cameras. Such images are known as geo-tagged images. The availability of such geographical context of images enables emerging several image-based smart city applications. Developing such smart city applications requires searching for images, among the massive amounts of collected images, especially to be used for training various machine learning algorithms. Thus, there is an immense need for a data management system for geo-tagged images.
Towards this end, it is paramount to build a data management system that organizes the images in structures that enable searching and retrieving the images efficiently and accurately. On one hand, the data management system should overcome the challenge of lacking an accurate spatial representation of legacy images that were collected without spatial metadata, as well as representing the content of an image accurately using an enriched visual descriptor. On the other hand, the system should also enable efficient storage of images utilizing both their spatial and visual properties and thus their retrieval based on spatial-visual queries. To address these challenges we present a system which includes three integrated modules: a) modeling an image spatially by its scene location using a data-centric approach, b) extending the visual representation of an image with the feature set of multiple similar images located in its vicinity, and c) designing index structures that expedite the evaluation of spatial-visual queries.

Location: 325

Audiences: Everyone Is Invited

Contact: Lizsl De Leon