Product Recommendation using Object Detection from Video, Based on Facial Emotions

Abstract

In today’s world, with the increasing demand of products and their growing productivity from producers, customers sometimes failed to decide whether they are interested in buying a particular product or not. So author, here proposed a framework which deals with the buying of only items of interest, for a consumer. In our feature-set, whenever any consumer tends to watch any video from YouTube, it results in breakdown into several frames (frames per second), and from there we use object detection technique to detect each and every object in a particular frame, and then to find whether our consumer is interested in that particular object or not, we use facial emotion detector to check whether our user is happy, surprised, neutral or any other emotion. After viewing those products which are present in a frame of a video. Merging only those items of interest which were tend to fall for consumer’s positive choices (emotions), we then used Amazon online marketing technique to recommend products selected by our framework.