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A computer vision library for human-computer interaction, focusing on head pose estimation, gaze direction, skin detection, motion tracking, and saliency mapping using CNNs.
What is Web?
Deepgaze is a computer vision library focused on human-computer interaction, providing tools for head pose estimation, gaze direction analysis, skin detection, motion tracking, and saliency mapping. It uses Convolutional Neural Networks (CNNs) and traditional algorithms to solve complex vision problems, such as estimating where a person is looking or detecting motion in video streams. The library simplifies implementing these advanced techniques, reducing development time for researchers and developers.
Computer vision researchers, developers working on robotics, surveillance systems, or interactive applications, and students learning about human-computer interaction and neural networks.
Deepgaze offers a unified, optimized library that combines CNNs with classic computer vision methods, enabling quick implementation of state-of-the-art algorithms. Its ease of use and comprehensive feature set make it a go-to choice for projects requiring robust human interaction capabilities without extensive coding effort.
Overview
Computer Vision library for human-computer interaction. It implements Head Pose and Gaze Direction Estimation Using Convolutional Neural Networks, Skin Detection through Backprojection, Motion Detection and Tracking, Saliency Map.
Use Cases
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