Context-based sketch classification

Abstract

Most of existing methods perform sketch classification by considering individually sketched objects and often fail to identify their correct categories, due to the highly abstract nature of sketches. We present a novel context-based sketch classification framework using relations extracted from scene images. For a sketched scene containing multiple objects, we propose to classify a sketched object by considering its surrounding context in the scene, which provides vital cues for alleviating its recognition ambiguity. We learn such context knowledge from a database of scene images by summarizing the inter-object relations therein, such as co-occurrence, relative positions and sizes. We show that the context information can be used for both incremental sketch classification and sketch co-classification. Our method outperforms a state-of-the-art single-object classification method, evaluated on a new dataset of sketched scenes.

Date of Award	2019
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology