In this paper, we unify C1 units and the locality preserving projections (LPP) into the conventional gist model for scene classification. For the improved gist model, we first utilize the C1 units, intensity channel and color channel of color image to represent the color image with the high dimensional feature, then we project high dimensional samples to a low dimensional subspace via LPP to preserve both the local geometry and the discriminate information, and finally, we apply the nearest neighbour rule with the Euclidean distance for classification. Experimental results based on the USC scene database not only demonstrate that the proposed gist improves the classification accuracy around 7% but also reduce the testing cost around 50 times in comparing with the original gist model proposed by Siagian and Itti in TPAMI 2007.
展开▼
