Object recognition based on human saccadic behaviour

The automated recognition of targets in complex backgrounds is a difficult problem, yet humans perform such tasks with ease. We therefore propose a re cognition model based on behavioural and physiological aspects of the human visual system. Emulating saccadic behaviour, an object is First memorised as a sequence of fixations. At each fixation an artificial visual field is constructed using a multi resolution/orientation Gabor filterbank, edge fea tures are extracted, and a new saccadic location is automatically selected. When a new image is scanned and a 'familiar' field of view encountered, th e memorised saccadic sequence is executed over the new image. If the expect ed visual field is found around each fixation point, the memorised object i s recognised. Results are presented from trials in which individual objects were first memorised and then searched for in collages of similar objects acting as distracters. In the different collages, entries of the memorised objects were subjected to various combinations of rotation, translation and noise corruption. The model successfully detected the memorised object in over 93% of the 'object present' trials, and correctly rejected collages in over 98% of the trials in which the object was not present in the collage. These results are compared with those obtained using a correlation-based r ecogniser, and the behavioural model is found to provide superior performan ce.