Figure 8.

The idea behind the features versus context approach is to learn to discriminate between the feature we wish to detect (e.g., a face, an eye, etc.) and poorly detected versions of it. This approach eliminates the classical overlapping of multiple detections around the object of interest at multiple scales. At the same time, it increases the accuracy of the detection because we are moving away from poor detections and toward precise ones.