Context Aware On-line Diagramming Recognition

This paper presents a context aware, online immediate-mode diagramming recognition and beautification software for hand-sketched diagrams. The system is independent of stroke-order, -number, -direction and is invariant to scaling, translation and rotation. In our stroke-based recognition model, we propose convexity features along with spatial and temporal proximity features to prune the combinatorial search space of possible stroke configurations to form shapes. This reduces the problem of exponential complexity to polynomial one while reducing the error by 24% compared to temporal proximity based criterion. The strokes are then recognized using geometric polygonal features against a neural-net based classifier for 17 classes. The diagramming system is based on stroke-based classifier combination model where an arbitrator makes context aware decisions using suggestions from shape, connector and writing-drawing experts. We achieved an accuracy of 92.7%, 81.4% and 91.5% on the respective experts for a collection of 700,000 online shapes.