In this case, 2 face-to-face users in the left and right directions are performing the copy gesture. An example of failing to identify the direction of 1 of 2 users is shown in Figure 17. Gesture recognition could fail here if the direction of 1 of the 2 users performing this gesture could not be identified. The overall average recognition rate of the copy gesture was approximately 85%. The recognition rate for the copy gesture by 8 subjects is shown in Figure 16. The system-usability evaluation was conducted on the basis of a questionnaire based on the System Usability Scale (SUS) evaluation method, to which we have added a section for open comments. The multi-touch gestures prepared for this system include an operation to change the direction of an object to face the user and a copy operation in which two users generate copies of an object in addition to basic touch gestures. By performing background differencing on the captured infrared images, the system establishes an association between the hand area and touch points and estimates the position of the user touching the table and the multi-touch gesture. Using an inexpensive FTIR touch panel and a set of infrared lights placed above the FTIR panel, the infrared camera obtains information on table touch areas and the shadow area of the hand when a user performs a touch operation. We also present the results of touch-gesture recognition accuracy experiments and a system-usability evaluation. In this paper, we describe a multi-touch tabletop system using infrared image recognition for user position identification that expands upon the previous system configuration and software we created. The system-usability evaluation revealed that prior learning was easy and that system operations could be easily performed. The multi-touch gestures prepared for this system include an operation to change the direction of an object to face the user and a copy operation in which two users generate duplicates of an object. Using an inexpensive FTIR touch panel and infrared light, this system picks up the touch areas and the shadow area of the user’s hand by an infrared camera to establish an association between the hand and table touch points and estimate the position of the user touching the table. This paper describes the development of a multi-touch tabletop system using infrared image recognition for user position identification and presents the results of touch-gesture recognition experiments and a system-usability evaluation. An effective method of recognizing user actions without placing a burden on the user would be some type of visual process, so the development of a method that processes multi-touch gestures by visual means is desired. The ability to identify the users touching the table and their positions can promote collaborative work among participants, so methods have been studied that involve attaching sensors to the table, chairs, or to the users themselves. A tabletop system can facilitate multi-user collaboration in a variety of settings, including small meetings, group work, and education and training exercises.
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