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An object classification method based on RGB-D features fusion is proposed in this paper. Firstly, image features in terms of texture, size, shape, from the RGB image and the depth image are extracted; secondly, the improved K-means clustering method is used to cluster the different extracted features to obtain seven different visual dictionaries respectively; then, the LLC coding model is used to perform feature coding on the extracted visual features to obtain seven different image feature expressions; meanwhile, above seven features expression are fused using the linear cascade mode to obtain the fusion feature; finally, linear SVM performs classifier is used to realize the object classification based on fusion feature. Experimental results show that compared with some existing algorithm based on RGB-D, the accuracy of our proposed method is increased to 87.3%. The accuracy of object classification is significantly improved.

Object classification based on RGB-D features fusion and LLC coding