المجلة الجزائرية للعلوم
Volume 7, Numéro 14, Pages 80-88
2021-06-03

Object Multi‐detection And Multi‐tracking Via Machine Learning And Deep Learning



Authors : Merouane Labeni . Chaouki Boufenar . Mokhtar Taffar .

Abstract

Objects detection and tracking in video frames constitute a vital field of research that provide appropriate information about objectsand their trajectories. An interesting technique to achieve these goals is using digital image/video processing methods with machine learning and deep learning methods. This paper presents an object multi-detection and multi-tracking approach based on a combination of machine learning methods,using KMeans clustering and silhouette coefficient measure that are used for objectmulti-detection with a deeper convolutional neural network method which represents a ConvNet architecture used for objectsclassification, and a proposed algorithm using a mathematical concept for object multi-tracking. This work demonstrates that the mission of object multi-detection and multi-tracking can be achieved via standard image/video processing and machine learning (consequently deep learning) methods. Therefore, and for both detection and tracking goals, we will show that optical flow analysis, data analysis and ConvNets architectures are well suited towards these goals.

Keywords

Image/Video Processing, Machine Learning, Deep Learning

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