Segmentation and Recognition of Offline Sketch Scenes Using Dynamic Programming

Sketch recognition aims to segment and identify objects in a collection of hand-drawn strokes. In general, segmentation is a computationally demanding process since it requires searching through a large number of possible recognition hypotheses. It has been shown that, if the drawing order of the strokes is known, as in the case of online drawing, a class of efficient recognition algorithms becomes applicable. In this article, we introduce a method that achieves efficient segmentation and recognition in offline drawings by combining dynamic programming with a novel stroke ordering method. Through rigorous evaluation, we demonstrate that the combined system is efficient as promised, and either beats or matches the state of the art in well-established databases and benchmarks.

Automated summary

This article introduces a method that combines dynamic programming with a novel stroke ordering method for efficient segmentation and recognition in offline drawings. Through rigorous evaluation, it is demonstrated that the combined system outperforms or matches the state of the art in established databases and benchmarks.