8 papers with code • 0 benchmarks • 1 datasets
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In particular, we adopt a region-based object detection structure with two carefully designed detectors to separately pay attention to the human body and body parts in a coarse-to-fine manner, which we call Detector-in-Detector network (DID-Net).
In this paper we focus on recognition of fingerspelling sequences in American Sign Language (ASL) videos collected in the wild, mainly from YouTube and Deaf social media.
Wearable cameras stand out as one of the most promising devices for the upcoming years, and as a consequence, the demand of computer algorithms to automatically understand the videos recorded with them is increasing quickly.
The recognition of hand gestures is a very interesting research topic due to the growing demand in recent years in robotics, virtual reality, autonomous driving systems, human-machine interfaces and in other new technologies.
In particular, the distance of the thumb and index fingertips is employed to scale a 3D object in virtual environment.
This paper describes the implementation of a control system based on ten different hand gestures, providing a useful approach for the implementation of better user-friendly human-machine interfaces.
One purpose of VR environments is to transform a virtual 3D object with affine parameters by using the gesture of thumb and index fingers.