Sketch retrieval aims at retrieving most similar sketches from a large database based on one hand-drawn query. Successful retrieval hinges on an effective representation of sketch images and an efficient search method. In this paper, we propose a representation scheme which takes sketch strokes into account with local features, thereby facilitating efficient retrieval with codebooks. Stroke features are detected via densely sampled points on stroke lines from which local gradients are further enhanced and described by a quantized histogram of gradients. A codebook is organized in a hierarchical vocabulary tree, which maintains structural information of visual words and enables efficient retrieval in sub-linear time. Experimental results on three data sets demonstrate the merits of the proposed algorithm for effective and efficient sketch retrieval.
|Publication status||Published - 2013 Jan 1|
|Event||2013 24th British Machine Vision Conference, BMVC 2013 - Bristol, United Kingdom|
Duration: 2013 Sep 9 → 2013 Sep 13
|Conference||2013 24th British Machine Vision Conference, BMVC 2013|
|Period||13/9/9 → 13/9/13|
All Science Journal Classification (ASJC) codes
- Computer Vision and Pattern Recognition