402 citations · 563 across the 8 of their papers we have counts for
8 papers
Deep Learning-Based Robust Multi-Object Tracking via Fusion of mmWave Radar and Camera Sensors
Lei Cheng, Arindam Sengupta, Siyang Cao
Autonomous driving holds great promise in addressing traffic safety concerns by leveraging artificial intelligence and sensor technology. Multi-Object Tracking plays a critical rol…
3D Radar and Camera Co-Calibration: A Flexible and Accurate Method for Target-based Extrinsic Calibration
Lei Cheng, Arindam Sengupta, Siyang Cao
Advances in autonomous driving are inseparable from sensor fusion. Heterogeneous sensors are widely used for sensor fusion due to their complementary properties, with radar and cam…
mmPose-NLP: A Natural Language Processing Approach to Precise Skeletal Pose Estimation using mmWave Radars
Arindam Sengupta, Siyang Cao
In this paper we presented mmPose-NLP, a novel Natural Language Processing (NLP) inspired Sequence-to-Sequence (Seq2Seq) skeletal key-point estimator using millimeter-wave (mmWave)…
mmFall: Fall Detection using 4D MmWave Radar and a Hybrid Variational RNN AutoEncoder
Feng Jin, Arindam Sengupta, Siyang Cao
In this paper we propose mmFall - a novel fall detection system, which comprises of (i) the emerging millimeter-wave (mmWave) radar sensor to collect the human body's point cloud a…
mm-Pose: Real-Time Human Skeletal Posture Estimation using mmWave Radars and CNNs
Arindam Sengupta, Feng Jin, Renyuan Zhang +1
In this paper, mm-Pose, a novel approach to detect and track human skeletons in real-time using an mmWave radar, is proposed. To the best of the authors' knowledge, this is the fir…
Multiple Patients Behavior Detection in Real-time using mmWave Radar and Deep CNNs
Feng Jin, Renyuan Zhang, Arindam Sengupta +4
To address potential gaps noted in patient monitoring in the hospital, a novel patient behavior detection system using mmWave radar and deep convolution neural network (CNN), which…