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With the evolution of information technology, devices such as smart TVs allow users to easily search for broadcast information, browse, participate in broadcasting, shop, etc. However, while watching, such additional information can be obstructive elements when seen by other people. Moreover, such smart functionalities cannot be utilized in public places. Therefore, in order to address the problem of the viewing disturbance element and formulate a method of providing the information, it is necessary to photograph the TV or the monitor screen using a smart device and immediately transmit the requisite information such as P2P information and advertisement information. We designed and implemented a system that allows confirmation. The proposed system minimizes interruption of viewing and presents a new user experience model so that anyone can easily use screenshots to generate additional information. A region of interest is extracted from a frame of a moving image photographed for efficiently searching for additional information such as the position information of the region of interest, the size information, and the projection information of the image edge of the region of interest. As a result of the experiment, it was confirmed that the additional information matched the video image shot using the smart device.

This study proposes a system that can recognize human emotional state from bio-signal. The technology is provided to improve the interaction between humans and computers to achieve an effective human–machine that is capable for intelligent interaction. The proposed method is able to recognize six emotional states, such as joy, happiness, fear, anger, despair, and sadness. These set of emotional states are widely used for emotion recognition purposes. The result shows that the proposed method can distinguish one emotion compared to all other possible emotional states. The method is composed of two steps: 1) multi-modal bio-signal evaluation and 2) emotion recognition using artificial neural network. In the first step, we present a method to analyze and fix human sensitivity using physiological signals, such as electroencephalogram, electrocardiogram, photoplethysmogram, respiration, and galvanic skin response. The experimental analysis shows that the proposed method has good accuracy performance and could be applied on many human–computer interaction devices for emotion detection.