• The Journal of the Korea Contents Association
• /
• v.19 no.8
• /
• pp.490-499
• /
• 2019

Face recognition payment service is an innovative payment method based on face recognition technology and is emerging in China now. Various industries regarding unmanned sales are likely to utilize this face recognition payment service in the future. This study investigated the factors influencing the usage intention of Chinese consumers who have experience using face recognition service. We used questionnaire survey and analysis with SPSS and AMOS. According to the results of the study, conclusions are as followed. First, consumers' attitudes toward the characteristic of face recognition payment service, which are non-contact and non-coercion, positively affected perceived usefulness. Second, the rapidness of the facial recognition payment among the recognition, the security and the rapidness of this service affected the ease of use. Third, social influences such as subjective norms also influence the intention to use. Fourth, the increase of the level of self-expression awareness and the intention of using face recognition payment service are confirmed. Through these results, the implications for design and communication of related innovative services were discussed.

• International Journal of Advanced Culture Technology
• /
• v.10 no.1
• /
• pp.230-235
• /
• 2022

This study is to select an optimal object detection algorithm for designing a self-checkout counter to improve the inconvenience of payment systems for products without existing barcodes. To this end, a performance comparison analysis of YOLO v2, Tiny YOLO v2, and the latest YOLO v5 among deep learning-based object detection algorithms was performed to derive results. In this paper, performance comparison was conducted by forming learning data as an example of 'donut' in a bakery store, and the performance result of YOLO v5 was the highest at 96.9% of mAP. Therefore, YOLO v5 was selected as the artificial intelligence object detection algorithm to be applied in this paper. As a result of performance analysis, when the optimal threshold was set for each donut, the precision and reproduction rate of all donuts exceeded 0.85, and the majority of donuts showed excellent recognition performance of 0.90 or more. We expect that the results of this paper will be helpful as the fundamental data for the development of an automatic payment system using AI self-service technology that is highly usable in the non-face-to-face era.

• International Journal of Advanced Culture Technology
• /
• v.9 no.2
• /
• pp.100-105
• /
• 2021

Contactless service is rapidly emerging as a new growth strategy due to consumers who are reluctant to the face-to-face situation in the global pandemic of coronavirus disease 2019 (COVID-19), and various technologies are being developed to support the fast-growing contactless service market. In particular, the restaurant industry is one of the most desperate industrial fields requiring technologies for contactless service, and the representative technical case should be a kiosk, which has the advantage of reducing labor costs for the restaurant owners and provides psychological relaxation and satisfaction to the customer. In this paper, we propose a solution to the restaurant's store operation through the unmanned kiosk using a state-of-the-art artificial intelligence (AI) technology of image recognition. Especially, for the products that do not have barcodes in bakeries, fresh foods (fruits, vegetables, etc.), and autonomous restaurants on highways, which cause increased labor costs and many hassles, our proposed system should be very useful. The proposed system recognizes products without barcodes on the ground of image-based AI algorithm technology and makes automatic payments. To test the proposed system feasibility, we established an AI vision system using a commercial camera and conducted an image recognition test by training object detection AI models using donut images. The proposed system has a self-learning system with mismatched information in operation. The self-learning AI technology allows us to upgrade the recognition performance continuously. We proposed a fully automated payment system with AI vision technology and showed system feasibility by the performance test. The system realizes contactless service for self-checkout in the restaurant business area and improves the cost-saving in managing human resources.

• Journal of Digital Convergence
• /
• v.18 no.7
• /
• pp.123-133
• /
• 2020

The aim of this study is to scrutinize acceptance intentions of Korean users and influences of information security related factors on mobile payment services based on biometric authentication methods, like finger print authentication or face recognition authentication, by focusing on ApplePay. Unlike previous studies on user acceptance of mobile payment which lack considerations on information security related factors, this study employs the UTAUT with detailed information security factors to create a research model and PLS(Partial Least Squares) method to analyze the model. Based on the analysis, gaining trust on service through company's efforts on information protection, personal characteristics and trust on applied security technologies are important factors to Korean users along with social awareness and service infrastructures. The result of this study would be helpful to companies or organizations, which provide biometric-based mobile payment services, to understand needs of Korean consumers. Based on this study, further analysis is expected to find impacts of user experiences on same company's or competitors' products to acceptance intentions.