217 citations · 565 across the 9 of their papers we have counts for
4 papers · 1 filter
Tracking Pedestrian Heads in Dense Crowd
Ramana Sundararaman, Cedric De Almeida Braga, Eric Marchand +1
Tracking humans in crowded video sequences is an important constituent of visual scene understanding. Increasing crowd density challenges visibility of humans, limiting the scalabi…
OpenTraj: Assessing Prediction Complexity in Human Trajectories Datasets
Javad Amirian, Bingqing Zhang, Francisco Valente Castro +3
Human Trajectory Prediction (HTP) has gained much momentum in the last years and many solutions have been proposed to solve it. Proper benchmarking being a key issue for comparing…
Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories with GANs
Javad Amirian, Jean-Bernard Hayet, Julien Pettre
This paper proposes a novel approach for predicting the motion of pedestrians interacting with others. It uses a Generative Adversarial Network (GAN) to sample plausible prediction…
Real-time Crowd Tracking using Parameter Optimized Mixture of Motion Models
Aniket Bera, David Wolinski, Julien Pettré +1
We present a novel, real-time algorithm to track the trajectory of each pedestrian in moderately dense crowded scenes. Our formulation is based on an adaptive particle-filtering sc…