A new framework for online sketch-based image retrieval in web environment
We present a novel framework for retrieval of images, based on the user's sketches performed in web environment. Unlike previous approaches, our method is capable of online retrieval and provides balanced trade-off between computational cost and robustness, while still preserving local properties. In our approach novel combination of features is introduced, which describes properties of desired results and query images. Based on the extracted features we use nearest neighbor recognizer, trained on dynamic neighborhoods, in combination with k-means and k-D tree technique for further speedup. A novel technique for online retrieval, based on sequential input processing and partial hierarchical score evaluation, is introduced, allowing us to suggest on the fly entries based on in-progress sketch. We tested our method on small and large scale databases and achieved promising results. The solution itself is implemented in collaborative environment, what allows users to produce queries cooperatively.