Abstract
Computer vision can be deemed as an emerging field which processes real world images in order to display a variety of numerical information about them. To improve the quality of the lifestyle that the visually impaired possess, we propose an assistive model which combines the various aspects of computer vision. Our proposed model aims at detecting the number of faces by using haar cascade classifiers and integrating it with Raspberry Pi. The processed images are run through the classifier and sum total is alerted through an auditory output via headphones. This model further boasts an average accuracy of 82.5%. Our model also notifies the visually impaired of the spatial orientation of the people surrounding them.
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