OM
O. Mazhar
5 records found
1
Authored
Intuitive user interfaces are indispensable to interact with the human centric smart environments. In this paper, we propose a unified framework that recognizes both static and dynamic gestures, using simple RGB vision (without depth sensing). This feature makes it suitable for i
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GEM
Glare or Gloom, I Can Still See You - End-to-End Multi-Modal Object Detection
Deep neural networks designed for vision tasks are often prone to failure when they encounter environmental conditions not covered by the training data. Single-modal strategies are insufficient when the sensor fails to acquire information due to malfunction or its design limit ...
Contributed
Handling the unknown
Towards on-the-job object recognition
As robots are becoming a more integral part in our daily lives, it is important to ensure they work in a safe and efficient manner. A large part of perceiving the environment is done through robot vision. Research in computer vision and machine learning lead to great improvements
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One Pose Fits All
A novel kinematic approach to 3D human pose estimation
3D human pose estimation is a widely researched computer vision task that could be applied in scenarios such as virtual reality and human-robot interaction. With the lack of depth information, 3D estimation from monocular images is an inherently ambiguous problem. On top of that,
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Tooth removal is one of the most performed surgical procedures worldwide. Despite the high amount of tooth removal procedures carried out each year, scientific understanding of these procedures is not present. Knowledge of force and torque behaviour is limited and knowledge about
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