Object Detection with Discriminatively Trained Part-Based Models
作者： P F Felzenszwalb , R B Girshick , D McAllester , D Ramanan
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摘要: … Brown University's Pedro Felzenszwalb and his colleagues described a method to find objects by managing these effects (“Object Detection with Discriminatively Trained Part-Based Models,” vol. 32, no. 9, 2010, pp. … Specifically, they built an object detector using the “sliding window” method. To search for, say, cars, the user would first build a classifier, which is a decision rule, learned from data, that can decide whether an image window contains a car or not. The user then takes a subwindow of the image, describes it with features that are …
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