@inproceedings{ae660c84eb1c40c1b7c2cab90580e4de,
title = "ShapeExplorer: Querying and exploring shapes using visual knowledge",
abstract = "With unprecedented amounts of multimodal data on the Internet, there is an increasing demand for systems with a more fine-grained understanding of visual data. ShapeExplorer is an interactive software tool based on a detailed analysis of images in terms of object shapes and parts. For instance, given an image of a donkey, the system may rely on previously acquired knowledge about zebras and dogs to automatically locate and label the head, legs, tail, and so on. Based on such semantic models, ShapeExplorer can then generate morphing animations, synthesize new shape contours, and support object part-based queries as well as clipart-based image retrieval.",
keywords = "Shape knowledge harvesting, Shape matching, Shape segmentation, Shape synthesis",
author = "Tong Ge and Yafang Wang and {De Melo}, Gerard and Zengguang Hao and Andrei Sharf and Baoquan Chen",
note = "Publisher Copyright: {\textcopyright} 2016, Copyright is with the authors.; 19th International Conference on Extending Database Technology, EDBT 2016 ; Conference date: 15-03-2016 Through 18-03-2016",
year = "2016",
month = jan,
day = "1",
doi = "10.5441/002/edbt.2016.70",
language = "English",
series = "Advances in Database Technology - EDBT",
publisher = "OpenProceedings.org",
pages = "648--651",
editor = "Ioana Manolescu and Evaggelia Pitoura and Amelie Marian and Sofian Maabout and Letizia Tanca and Georgia Koutrika and Kostas Stefanidis",
booktitle = "Advances in Database Technology - EDBT 2016",
}