Rinaldi Munir
The development of technology and human needs regarding the security and convenience aspects encourage the installed supervisory cameras in certain areas such as the Mandiri Cash Machines, advertising displays, office entrances, shopping centers, housing and locations that require special supervision. Demographic data is one of the data needed to analyze businesses especially in the shopping center area and interactive advertising display. Information about demographic data, especially gender, can be automatically presented through supervisory video data processing. Some of the characteristics of soft-biometric which are commonly used can be extracted from humans where some of these characteristics are characteristics found on the human face (Dantcheva, et al., 2011). The initial stages of the study using facial image data from commonly used data-sets and extracted demographic data is gender. The purpose of this study was the initial stage of developing a program that could calculate demographic data with input in the form of a video of the supervisor. In the initial stage of the program input is limited in the form of facial images of data-sets commonly used with gender-in-form. The method applied in this study includes: 1) Face detection adopts Viola and Jones Engineering, 2011, 2) Extraction Characteristics Applying Pyramid Multi-Level Bekhouche Features, et al., 2017, 3) Gender Classification Using K-Nearest Neighbour and / or Support Vector Machine.
Prototype gender classification program based on face recognition (Matlab scale) and publication on the proceedings of the international conference.
How to extract demographic data through processing video camera supervisors. The demographic data obtained can be used for business analysis needs, for example on the interactive ad display where the displays shown will be adjusted to the demographic data of people who see ad displays.