Human can effortlessly recognise objects from fragments of image contour.
ICCV 2005 paper shows how an automatic system can exploit contour as a powerful cue for image classification and categorical object detection.
An improved multi-scale version of this work by Jamie Shotton, Multi-Scale Categorical Object Recognition Using Contour Fragments
Example object detection results on the Weizmann horse database. Green boxes represent correct detections of the horses, red boxes are false positives, and yellow boxes are false negatives. The fragments of contour used for detection are visualised in the final column.
More contour visualisations. This technique was applied to a 17 object class database from TU Graz. Here are a few examples where the contour fragments used for detection are superimposed.