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 sk...[ Read more ]

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.