An Incremental Learning Method Based on SVM for Online Sketchy Shape Recognition

This paper presents briefly an incremental learning method based on SVM for online sketchy shape recognition. It can collect all classified results corrected by user and select some important samples as the retraining data according to their distance to the hyper-plane of the SVM-classifier. The classifier can then do incremental learning quickly on the newly added samples, and the retrained classifier can be adaptive to the user's drawing styles. Experiment shows the effectiveness of the proposed method.