Pictorial Structures for Object Recognition and Part Labeling in Drawing

Although the sketch recognition and computer vision communities attempt to solve similar problems in different domains, the sketch recognition community has not utilized many of the advancements made in computer vision algorithms. In this paper we propose using a pictorial structure model for object detection, and modify it to better perform in a drawing setting as opposed to photographs. By using this model we are able to detect a learned object in a general drawing, and correctly label its parts. We show our results on 4 categories.

 

Fig 1. Example of the input (a) and output (b) of the algorithm. Note that background strokes for each detector are successfully removed by our algorithm.