The document discusses object class detection in images. It describes how algorithms like SIFT and HOG can be used to detect interest points and describe features in images. These features can then be encoded using bag-of-features to represent images. Object class detection involves classifying and localizing objects within images. The document outlines methods used and evaluation metrics like recall, precision and average precision used in competitions like Pascal VOC to evaluate algorithms for object class detection tasks.