PoseShop: Human Image Database Construction and Personalized Content Synthesis

Chen, Tao, Tan, Ping, Ma, Li-Qian, Cheng, Ming-Ming, Shamir, Ariel and Hu, Shi-Min ORCID: https://orcid.org/0000-0001-7507-6542 2013. PoseShop: Human Image Database Construction and Personalized Content Synthesis. IEEE Transactions on Visualization and Computer Graphics 19 (5) , pp. 824-837. 10.1109/TVCG.2012.148

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Abstract

We present PoseShop2014: a pipeline to construct segmented human image database with minimal manual intervention. By downloading, analyzing, and filtering massive amounts of human images from the Internet, we achieve a database which contains 400 thousands human figures that are segmented out of their background. The human figures are organized based on action semantic, clothes attributes, and indexed by the shape of their poses. They can be queried using either silhouette sketch or a skeleton to find a given pose. We demonstrate applications for this database for multiframe personalized content synthesis in the form of comic-strips, where the main character is the user or his/her friends. We address the two challenges of such synthesis, namely personalization and consistency over a set of frames, by introducing head swapping and clothes swapping techniques. We also demonstrate an action correlation analysis application to show the usefulness of the database for vision application.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords:	Image database, image composition
Publisher:	IEEE
ISSN:	1077-2626
Last Modified:	24 Oct 2022 10:45
URI:	https://orca.cardiff.ac.uk/id/eprint/45768

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