17HS4800, The Development of 3D Content Creation, Authoring and Printing Technology Based on Mobile Platform and Application,
Choi Jin Sung
Abstract
Various interfaces have been suggested for mobile devices, including touch gesture and embedded sensor-based interfaces. However, if a user's task requires a thorough look, these interfaces hinder sight of view in display and thus can be inappropriate for the tasks. This problem is more important especially in the mobile computer aided design (CAD) context, which performs visually demanding tasks on the limited screen. To address this point, this study suggests a mobile interface utilizing the rear camera of the device and describes the function mapping for CAD. The suggested interface detects finger attachment and movement direction. The number of colors in camera vision and local binary pattern are used as features, and a support vector machine (SVM) is used for feature classification. A prototype application is designed for validation, and appropriate SVM models are selected through benchmarking tests. The validation results show that the suggested interface can perform with high accuracy and low computational resources.
KSP Keywords
Camera vision, Computer-aided design, Embedded sensor, Feature Classification, Finger gesture, Function mapping, Gesture Input, High accuracy, Local binary Pattern, Mobile devices, Mobile interfaces
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