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Hand gestures provide a natural and an intuitive way of user interaction in AR/VR applications. However, the most popular and commercially available devices such as the Google Cardboard and Wearality1 still employ only primitive modes of interaction such as the magnetic trigger, conductive lever and have limited user-input capability. The truly instinctual gestures work only with inordinately priced...
Wearable Augmented Reality (AR) devices1 are being explored in many applications for visualizing real-time contextual information. More importantly, these devices can also be used in tele-assistance from remote sites when on-field operators require off-field expert's guidance for trouble-shooting. For an effective communication, touchless hand gestures are the most intuitive to select a Region Of...
The future of user interfaces will be dominated by hand gestures. In this paper, we explore an intuitive hand gesture based interaction for smartphones having a limited computational capability. To this end, we present an efficient algorithm for gesture recognition with First Person View (FPV), which focuses on recognizing a four swipe model (Left, Right, Up and Down) for smartphones through single...
The existing, sophisticated AR gadgets1 in the market today are mostly exorbitantly priced. This limits their usage for the upcoming academic research institutes and also their reach to the mass market in general. Among the most popular and frugal head mounts, Google Cardboard (GC) and Wearality2 are video-see-through devices that can provide immersible AR and VR experiences with a smartphone. Stereo-rendering...
With the advancement in camera technologies and data streaming protocols, AR based applications are proving to be an important aid for inspection, training and supervision tasks in various operations including automotive industry, education etc. We demonstrate an AR based re-configurable inspection framework that can be utilized in cross-domain applications such as maintenance and repair assistance...
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