Relevance Feedbacks Algorithm Based on Locality Preserving Projections

Feedback Locality Preserving Projections (FLPP) incorporates user’s feedbacks into LPP. By properly disposing user’s feedbacks, FLPP can update the eigenvectors which span the image representation subspace, so we can obtain a semantic subspace which can better reflect intrinsic property of image data. FLPP can use user’s feedbacks to optimize rapidly image representation, so gain capability of long-term learning. Experimental results show that FLPP can effectively improve retrieval accuracy, and after long-term learning, an approximate optimal subspace can be obtained.