Object detection methods need as in

Object detection methods need as input a “region proposal system” that produces a set of sparse (for example selective search (Anon.)*) or a dense (for example features used in deformable part models (Anon.)*) set of features. The first version of the R-CNN system used the selective search method for generating region proposal. In the current version (known as “Faster R-CNN”), a “sliding window” based technique (described in the previous section) is used to generate a set of dense candidate regions and then a neural network driven region proposal network is used to rank region proposals according to the probability of a region containing a foreground object. The region proposal layer has two goals:From a list of anchors, identify background and foreground anchorsModify the position, width and height of the anchors by applying a set of “regression coefficients” to improve the quality of the anchors (for example, make them fit the boundaries of objects better)The region proposal layer consists of a Region Proposal Network and three layers – Proposal Layer, Anchor Target Layer and Proposal Target Layer. These three layers are described in detail in the following sections.