This paper is concerned with the development of techniques for the recognition of ornamental characters motivated by the perceptual processes involved in humans. To understand the perceptual process, we have performed the eye-tracking experiment to recognize the special set of characters, with artistic variations in character structure and form. The novelty of this paper is the use of human visual fixations to supervise the intermediate layers of the convolutional neural network. From the results obtained, we found that the network performs better when trained with the assistance of fixation information compared to the network trained without eye fixations.