83 citations · 203 across the 8 of their papers we have counts for
8 papers
BiPOCO: Bi-Directional Trajectory Prediction with Pose Constraints for Pedestrian Anomaly Detection
Asiegbu Miracle Kanu-Asiegbu, Ram Vasudevan, Xiaoxiao Du
We present BiPOCO, a Bi-directional trajectory predictor with POse COnstraints, for detecting anomalous activities of pedestrians in videos. In contrast to prior work based on feat…
Leveraging Trajectory Prediction for Pedestrian Video Anomaly Detection
Asiegbu Miracle Kanu-Asiegbu, Ram Vasudevan, Xiaoxiao Du
Video anomaly detection is a core problem in vision. Correctly detecting and identifying anomalous behaviors in pedestrians from video data will enable safety-critical applications…
Coupling Intent and Action for Pedestrian Crossing Behavior Prediction
Yu Yao, Ella Atkins, Matthew Johnson Roberson +2
Accurate prediction of pedestrian crossing behaviors by autonomous vehicles can significantly improve traffic safety. Existing approaches often model pedestrian behaviors using tra…
BiTraP: Bi-directional Pedestrian Trajectory Prediction with Multi-modal Goal Estimation
Yu Yao, Ella Atkins, Matthew Johnson-Roberson +2
Pedestrian trajectory prediction is an essential task in robotic applications such as autonomous driving and robot navigation. State-of-the-art trajectory predictors use a conditio…
Stochastic Sampling Simulation for Pedestrian Trajectory Prediction
Cyrus Anderson, Xiaoxiao Du, Ram Vasudevan +1
Urban environments pose a significant challenge for autonomous vehicles (AVs) as they must safely navigate while in close proximity to many pedestrians. It is crucial for the AV to…
Bio-LSTM: A Biomechanically Inspired Recurrent Neural Network for 3D Pedestrian Pose and Gait Prediction
Xiaoxiao Du, Ram Vasudevan, Matthew Johnson-Roberson
In applications such as autonomous driving, it is important to understand, infer, and anticipate the intention and future behavior of pedestrians. This ability allows vehicles to a…
Multi-Resolution Multi-Modal Sensor Fusion For Remote Sensing Data With Label Uncertainty
Xiaoxiao Du, Alina Zare
In remote sensing, each sensor can provide complementary or reinforcing information. It is valuable to fuse outputs from multiple sensors to boost overall performance. Previous sup…
Multiple Instance Choquet Integral Classifier Fusion and Regression for Remote Sensing Applications
Xiaoxiao Du, Alina Zare
In classifier (or regression) fusion the aim is to combine the outputs of several algorithms to boost overall performance. Standard supervised fusion algorithms often require accur…