New 3D Objects Retrieval Approach using Multi Agent Systems and Artificial Neural Network

Content-based 3D object retrieval is a substantial research area that has drawn a significant number of scientists in last couple of decades. Due to the rapid advancement of technology, 3D models are more and more accessible yet it is hard to find, the models we are searching for. This created the need for efficient and robust retrieval methods, allowing the extraction of relevant matches from the human perspective. Hence, in this paper we are proposing a new framework for 3D object retrieval that starts with a pre-treatment consisting of an Artificial Neural Network (ANN) algorithm with Histogram of features, allowing us to extract a representative value for each category of the database. These values are used for the Multi Agents System (MAS). In this phase, we are classifying these categories according to their relevance to the request object. This sets a distinguishing weight for each object of the database allowing us to extract the right matches. Experiments have proven the stringent of this approach.

@article{Sirbal2018,
  title     = {New 3D Objects Retrieval Approach using Multi Agent Systems and Artificial Neural Network},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {12},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Basma Sirbal and Mohcine Bouksim and Khadija Arhid and Fatima Rafii Zakani and Taoufiq Gadi},
  doi       = {10.14569/IJACSA.2018.091257},
  url       = {https://doi.org/10.14569/IJACSA.2018.091257}
}