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The problem of object detection in image and video has been treated by a large number of researchers. Many design factors degrade the reliability of the problem solutions, such as manual modeling of the object, manual features selection, handcrafting architecture, and learning algorithm selection. Here, a generalized object detection and localization system is presented. It has the ability to learn...
The system presented in this paper finds images and line-drawings in scanned pages; it is a crucial processing step in the creation of a large-scale system to detect and index images found in books and historic documents. Within the scanned pages that contain both text and images, the images are found through the use of SIFT-based local-features applied to the complete scanned-page. This is followed...
In this paper we discuss the issue of classifiers combined with histogram of oriented gradients (HOG) descriptors for human detection. And we present a method that combines AdaBoost learning with HOG descriptors. The weak learners used in our algorithm are based on weighted modified quadratic discriminant functions (MQDF) which is a parametric model. We evaluate our algorithm on the INRIA person dataset...
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