233 citations · 780 across the 34 of their papers we have counts for
5 papers · 2 filters
Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs
Rohan Chandra, Tianrui Guan, Srujan Panuganti +4
We present a novel approach for traffic forecasting in urban traffic scenarios using a combination of spectral graph analysis and deep learning. We predict both the low-level infor…
GraphRQI: Classifying Driver Behaviors Using Graph Spectrums
Rohan Chandra, Uttaran Bhattacharya, Trisha Mittal +3
We present a novel algorithm (GraphRQI) to identify driver behaviors from road-agent trajectories. Our approach assumes that the road-agents exhibit a range of driving traits, such…
DensePeds: Pedestrian Tracking in Dense Crowds Using Front-RVO and Sparse Features
Rohan Chandra, Uttaran Bhattacharya, Aniket Bera +1
We present a pedestrian tracking algorithm, DensePeds, that tracks individuals in highly dense crowds (greater than 2 pedestrians per square meter). Our approach is designed for vi…
RobustTP: End-to-End Trajectory Prediction for Heterogeneous Road-Agents in Dense Traffic with Noisy Sensor Inputs
Rohan Chandra, Uttaran Bhattacharya, Christian Roncal +2
We present RobustTP, an end-to-end algorithm for predicting future trajectories of road-agents in dense traffic with noisy sensor input trajectories obtained from RGB cameras (eith…
RoadTrack: Realtime Tracking of Road Agents in Dense and Heterogeneous Environments
Rohan Chandra, Uttaran Bhattacharya, Tanmay Randhavane +2
We present a realtime tracking algorithm, RoadTrack, to track heterogeneous road-agents in dense traffic videos. Our approach is designed for traffic scenarios that consist of diff…