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


Kshitiz Badola1, Ajay Joshi2 and Deepesh Sengar3, 1Guru Gobind Singh Indraprastha University, India, 2Deen Dayal Upadhyaya College (University of Delhi), India, 3Riga Technical University, Latvia


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.


Convolutional Neural Networks, Facial Expressions, Object Detection, ImageAI, Selenium, Machine Learning.

Full Text  Volume 10, Number 20