关键词：计算机视觉；图像识别系统；图像分类器
摘 要：We address various issues in learning and representation of visual object categories. A key componentof many state of the art object detection and image recognition systems, is the image classifier.e first show that a large number of classifiers used in computer vision that are based on comparisonof histograms of low level features, are “additive”, and propose algorithms that enable training and evaluation of additive classifiers that offer better tradeoffs between accuracy, runtime memoryand time complexity than previous algorithms. Our analysis speeds up the training and evaluation of several state of the art object detection, and image classification methods by several orders ofmagnitude.