Customer face analysis for retail analytics | |
| Author | Karim, Nabil Tahmidul |
| Call Number | AIT Thesis no.CS-17-02 |
| Subject(s) | Machine learning Artificial intelligence Neural networks (Computer science) Consumer satisfaction |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Computer Science, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Thesis ; no. CS-17-02 |
| Abstract | Customer experience, feedback and keeping a customer engaging surrounding are influential factors for any retail store. Acknowledging these facts enhance the development of businesses. Acquiring constructive statistics about customer interests can be extremely valuable for retail stores. This thesis aims to provide such information through an automated system using deep learning methodology. In this thesis, I present an automated system where face detection and tracking are done to retrieve faces of customers coming to retail stores. Afterwards, Siamese convolutional neural network is used to determine if its an old or a new customer. Then I use the same face image to identify the person’s age and gender through two more convolutional neural networks. At every frame, another convolutional neural network is used to identify the person’s sentiment and record it in the database. A series of individual experiments show that each of the network achieve satisfactory results. This prototype can provide a base for further research into using face features for retail analytics |
| Year | 2017 |
| Corresponding Series Added Entry | Asian Institute of Technology. Thesis : no. CS-17-02 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Computer Science (CS) |
| Chairperson(s) | Dailey, Matthew N.; |
| Examination Committee(s) | Mongkol Ekpanyapong;Vatcharaporn Esichaikul; |
| Scholarship Donor(s) | Asian Institute of Technology Fellowship; |
| Degree | Thesis (M. Eng.) - Asian Institute of Technology, 2017 |