An Approach for Detection of Entities in Dynamic Media Contents

Nzakiese Mbongo, Ngombo Armando
12/9/2025
cs.CV

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Abstract

The notion of learning underlies almost every evolution of Intelligent Agents. In this paper, we present an approach for searching and detecting a given entity in a video sequence. Specifically, we study how the deep learning technique by artificial neuralnetworks allows us to detect a character in a video sequence. The technique of detecting a character in a video is a complex field of study, considering the multitude of objects present in the data under analysis. From the results obtained, we highlight the following, compared to state of the art: In our approach, within the field of Computer Vision, the structuring of supervised learning algorithms allowed us to achieve several successes from simple characteristics of the target character. Our results demonstrate that is new approach allows us to locate, in an efficient way, wanted individuals from a private or public image base. For the case of Angola, the classifier we propose opens the possibility of reinforcing the national security system based on the database of target individuals (disappeared, criminals, etc.) and the video sequences of the Integrated Public Security Centre (CISP).

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Cite this paper

@article{mbongo2025approach,
  title  = {An Approach for Detection of Entities in Dynamic Media Contents},
  author = {Nzakiese Mbongo and Ngombo Armando},
  year   = {2025},
  eprint = {2512.09011},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2512.09011v1}
}

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