相关论文: Tesla-Rapture: A Lightweight Gesture Recognition S…
Collaborative robotic systems will be a key enabling technology for current and future industrial applications. The main aspect of such applications is to guarantee safety for humans. To detect hazardous situations, current commercially…
Positional estimation is of great importance in the public safety sector. Emergency responders such as fire fighters, medical rescue teams, and the police will all benefit from a resilient positioning system to deliver safe and effective…
The ability to predict motion in real time is fundamental to many maneuvering activities in animals, particularly those critical for survival, such as attack and escape responses. Given its significance, it is no surprise that motion…
Millimeter Waves (mmWave) systems have the potential of enabling multi-gigabit-per-second communications in future Intelligent Transportation Systems (ITSs). Unfortunately, because of the increased vehicular mobility, they require frequent…
Millimeter-wave (mmWave) radar enables contactless respiratory sensing,yet fine-grained monitoring is often degraded by nonstationary interference from body micromotions.To achieve micromotion interference removal,we propose…
Passive radars (PRs) provide a low-cost and energy-efficient approach to object detection by reusing existing wireless transmissions instead of emitting dedicated probing signals. Yet, conventional passive systems require prior knowledge of…
Millimeter-wave (mmWave) technology is increasingly recognized as a pivotal technology of the sixth-generation communication networks due to the large amounts of available spectrum at high frequencies. However, the huge overhead associated…
Autonomous driving systems rely on panoptic driving perception that requires both precision and real-time performance. In this work, we propose RMT-PPAD, a real-time, transformer-based multi-task model that jointly performs object…
Using 3D point clouds in odometry estimation in robotics often requires finding a set of correspondences between points in subsequent scans. While there are established methods for point clouds of sufficient quality, state-of-the-art still…
Millimeter-wave (mmw) radar is indispensable for Intelligent Transportation Systems (ITS), which can monitor traffic conditions in all weathers. An end-to-end simulation method for mmw radar monitoring and identification at traffic…
In this paper, we demonstrate the ability to recognize hand gestures in a non-contact, wireless fashion using only incoherent light signals reflected from a human subject. Fundamentally distinguished from radar, lidar and camera-based…
With the rapid development of the Internet of Things (IoT) and the rise of 5G communication networks and automatic driving, millimeter wave (mmWave) sensing is emerging and starts impacting our life and workspace. mmWave sensing can sense…
Robust and accurate trajectory estimation of mobile agents such as people and robots is a key requirement for providing spatial awareness for emerging capabilities such as augmented reality or autonomous interaction. Although currently…
Haptic perception is highly important for immersive teleoperation of robots, especially for accomplishing manipulation tasks. We propose a low-cost haptic sensing and rendering system, which is capable of detecting and displaying surface…
We discuss methods for teaching systems to identify gestures such as head nod and shake. We use iPhone X depth camera to gather data and later use similar data as input for a working app. These methods have proved robust for training with…
Surgical gesture recognition is important for surgical data science and computer-aided intervention. Even with robotic kinematic information, automatically segmenting surgical steps presents numerous challenges because surgical…
Robots and autonomous vehicles should be aware of what happens in their surroundings. The segmentation and tracking of moving objects are essential for reliable path planning, including collision avoidance. We investigate this estimation…
Gesture recognition using low-resolution instantaneous HD-sEMG images opens up new avenues for the development of more fluid and natural muscle-computer interfaces. However, the data variability between inter-session and inter-subject…
Wearable e-textile interfaces require gesture recognition capabilities but face severe constraints in power consumption, computational capacity, and form factor that make traditional deep learning impractical. While lightweight…
Human gesture recognition has assumed a capital role in industrial applications, such as Human-Machine Interaction. We propose an approach for segmentation and classification of dynamic gestures based on a set of handcrafted features, which…