Multi Moving Objects Detection in Video Using Pre-trained Deep Convolutional Neural Networks

Multi Moving Objects Detection in Video Using Pre-trained Deep Convolutional Neural Networks

Object Tracking; Video processing; Deep neural network; K-mean clustering.

Abstract- Nowadays object tracking is a critical concern in the field of machine vision. With the advent of powerful computers, affordable cameras, and growing demand for automatic video analysis, researchers have shown significant interest in object tracking. Various methods have been proposed for tracking objects in machine vision, but a key challenge remains: ensuring the robustness of tracking algorithms across consecutive video frames. In recent years, deep neural networks have emerged as a promising approach for accurate position estimation. In this study, we propose an enhanced method that combines deep convolutional neural networks with established techniques like K-means clustering. Our approach addresses challenges such as object disappearances and severe displacements. The selection of deep neural networks is motivated by their compatibility with target identification in video sequences, and achieving a remarkably low error rate in tracking validates our claim.

Abolfazl Ansaripour, Hosein Mahvash Mohamadi,

www.ijcit.com

December 2024

peri irawan

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