A comparative study of batch ensemble for multi-object tracking approximations in embedded vision

2021 ◽  
Author(s):  
Robert Nsinga ◽  
Stephen Karungaru ◽  
Kenji Terada
Keyword(s):  
Comparative Study ◽  
Object Tracking ◽  
Embedded Vision

scholarly journals Optimisation of a Siamese Neural Network for Real-Time Energy Efficient Object Tracking

2020 ◽  
Author(s):  
Dominika Przewlocka ◽  
Mateusz Wasala ◽  
Hubert Szolc ◽  
Krzysztof Blachut ◽  
Tomasz Kryjak
Keyword(s):  
Neural Network ◽  
Object Tracking ◽  
Real Time ◽  
Video Stream ◽  
Visual Object ◽  
Vision Systems ◽  
Embedded Vision ◽  
Network Training ◽  
Binary Networks ◽  
Embedded Vision Systems

In this paper the research on optimisation of visual object tracking using a Siamese neural network for embedded vision systems is presented. It was assumed that the solution shall operate in real-time, preferably for a high resolution video stream, with the lowest possible energy consumption. To meet these requirements, techniques such as the reduction of computational precision and pruning were considered. Brevitas, a tool dedicated for optimisation and quantisation of neural networks for FPGA implementation, was used. A number of training scenarios were tested with varying levels of optimisations-from integer uniform quantisation with 16 bits to ternary and binary networks. Next, the influence of these optimisations on the tracking performance was evaluated. It was possible to reduce the size of the convolutional filters up to 10 times in relation to the original network. The obtained results indicate that using quantisation can significantly reduce the memory and computational complexity of the proposed network while still enabling precise tracking, thus allow to use it in embedded vision systems. Moreover , quantisation of weights positively affects the network training by decreasing overfitting.

Object tracking based on harmony search: comparative study

2012 ◽  
Vol 21 (4) ◽  
pp. 043001-1 ◽  
Author(s):  
Ming-Liang Gao ◽  
Xiao-Hai He ◽  
Dai-Sheng Luo ◽  
Yan-Mei Yu
Keyword(s):  
Comparative Study ◽  
Object Tracking ◽  
Harmony Search

scholarly journals Low-cost multiple object tracking for embedded vision applications

2019 ◽  
Vol 27 (3) ◽  
pp. 1737-1751
Author(s):  
M. Imran SHEHZAD ◽  
Fazal Wahab KARAM ◽  
Shoaib AZMAT
Keyword(s):  
Object Tracking ◽  
Low Cost ◽  
Multiple Object Tracking ◽  
Embedded Vision ◽  
Multiple Object

scholarly journals Six Object Tracking Algorithms: A Comparative Study

2016 ◽  
Vol 9 (30) ◽  
Author(s):  
Vaibhav Kumar Agarwal ◽  
N. Sivakumaran ◽  
V. P. S. Naidu
Keyword(s):  
Comparative Study ◽  
Object Tracking ◽  
Tracking Algorithms
Sign in / Sign up

Export Citation Format

Share Document