Persistent Objects Tracking Across Multiple Non Overlapping Cameras

2005 ◽  
Author(s):  
Jinman Kang ◽  
Isaac Cohen ◽  
Gerard Medioni
Keyword(s):  
Objects Tracking

Real-Time Moving Objects Tracking for Distributed Smart Video Surveillances

2016 ◽  
Vol 11 (4) ◽  
pp. 324
Author(s):  
Nor Nadirah Abdul Aziz ◽  
Yasir Mohd Mustafah ◽  
Amelia Wong Azman ◽  
Amir Akramin Shafie ◽  
Muhammad Izad Yusoff ◽  
...  
Keyword(s):  
Real Time ◽  
Moving Objects ◽  
Objects Tracking

scholarly journals Multiple objects tracking in the UAV system based on hierarchical deep high-resolution network

2021 ◽  
Author(s):  
Wei Huang ◽  
Xiaoshu Zhou ◽  
Mingchao Dong ◽  
Huaiyu Xu
Keyword(s):  
High Resolution ◽  
Object Tracking ◽  
High Performance ◽  
State Of The Art ◽  
Class Imbalance ◽  
Unified Framework ◽  
Multiple Objects ◽  
Tracking Process ◽  
Objects Tracking ◽  
Different Types

AbstractRobust and high-performance visual multi-object tracking is a big challenge in computer vision, especially in a drone scenario. In this paper, an online Multi-Object Tracking (MOT) approach in the UAV system is proposed to handle small target detections and class imbalance challenges, which integrates the merits of deep high-resolution representation network and data association method in a unified framework. Specifically, while applying tracking-by-detection architecture to our tracking framework, a Hierarchical Deep High-resolution network (HDHNet) is proposed, which encourages the model to handle different types and scales of targets, and extract more effective and comprehensive features during online learning. After that, the extracted features are fed into different prediction networks for interesting targets recognition. Besides, an adjustable fusion loss function is proposed by combining focal loss and GIoU loss to solve the problems of class imbalance and hard samples. During the tracking process, these detection results are applied to an improved DeepSORT MOT algorithm in each frame, which is available to make full use of the target appearance features to match one by one on a practical basis. The experimental results on the VisDrone2019 MOT benchmark show that the proposed UAV MOT system achieves the highest accuracy and the best robustness compared with state-of-the-art methods.

Multiple small objects tracking based on dynamic Bayesian networks with spatial prior

Optik ◽  
2014 ◽  
Vol 125 (10) ◽  
pp. 2243-2247 ◽  
Author(s):  
Rui Yao ◽  
Yanning Zhang ◽  
Yong Zhou ◽  
Shixiong Xia
Keyword(s):  
Bayesian Networks ◽  
Dynamic Bayesian Networks ◽  
Objects Tracking
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