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Object recognition based on human saccadic behaviour
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PRE
AI
DOI：10.1007/s100440050033.png)
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Abstract
En 中文
The automated recognition of targets in complex backgrounds is a difficult problem, yet humans perform such tasks with ease. We therefore propose a recognition 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 features are extracted, and a new saccadic location is automatically selected. When a new image is scanned and a 'familiar' field of view encountered, the memorised saccadic sequence is executed over the new image. If the expected visual field is found around each fixation point, the memorised object is 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 recogniser, and the behavioural model is found to provide superior performance.
Keywords:
computer vision
object recognition
saccadic behaviour
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