Multiple pedestrian tracking under first-person perspective using deep neural network and social force optimization
Y Xue, Z Ju - Optik, 2021 - Elsevier
Multiple pedestrian tracking in the first-person perspective is a challenging problem,
obstacles of which are mainly caused by camera moving, frequent occlusions, and collision …
obstacles of which are mainly caused by camera moving, frequent occlusions, and collision …
A robust real-time detecting and tracking framework for multiple kinds of unmarked object
X Lv, C Dai, L Chen, Y Lang, R Tang, Q Huang, J He - Sensors, 2019 - mdpi.com
A rodent real-time tracking framework is proposed to automatically detect and track multi-
objects in real time and output the coordinates of each object, which combines deep …
objects in real time and output the coordinates of each object, which combines deep …
Tracking multiple indistinguishable and deformable objects based on multi-anchor flow with annular sector model
B Guo, Y Zhu - IEEE Access, 2019 - ieeexplore.ieee.org
Most of current multi-object tracking (MOT) methods solve the task of identity assignment
mainly by using the distinguishable features and predictable motions of nearly rigid objects …
mainly by using the distinguishable features and predictable motions of nearly rigid objects …
[引用][C] Optimized Deep LSTM-Based Multi-Object Tracking With Occlusion Handling Mechanism
SV Sokashe-Ghorpade, SA Pardeshi - International Journal of …, 2024 - World Scientific
The multi-object tracking is a basic computer vision process having a huge class of real-life
tools that range from monitoring of medical video to surveillance. The goal of tracking …
tools that range from monitoring of medical video to surveillance. The goal of tracking …