Image retrieval using object template

How to mine, organize and use the information of the objects in an image, which can just reflect the user's intension precisely, is overlooked for a long time. From the point of view of mining, training and utilizing such information efficiently, this paper focuses on a particular group of features for every class of object. With this group of features, the class of object can be separated with others most distinctly. Based on this idea, using SVM (Support Vector Machine), HGM (Hybrid Gauss Model), PCA (principle component analysis) and FFC (Forward Feature Combination), we design and implement an Object Template that can represent a kind of object (such as tiger) perfectly and then present its two applications. With our Object Template, the Recall Precision (P100) for image retrieval can be increased to 46.175%; the precision of Object Detection also reaches 82.832%. (On 3400 real-world image collections)