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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Abdelmajid Badri
Laboratory of Electronics, Energy, Automation & Information Processing, Faculty of Sciences and Techniques Mohammedia, University Hassan II Casablanca, Mohammedia, Morocco
Computer Science & IT Engineering

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Large-scale image-to-video face retrieval with convolutional neural network features Imane Hachchane; Abdelmajid Badri; Aïcha Sahel; Yassine Ruichek
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 1: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (341.601 KB) | DOI: 10.11591/ijai.v9.i1.pp40-45

Abstract

Convolutional neural network features are becoming the norm in instance retrieval. This work investigates the relevance of using an of the shelf object detection network, like Faster R-CNN, as a feature extractor for an image-to-video face retrieval pipeline instead of using hand-crafted features. We use the objects proposals learned by a Region Proposal Network (RPN) and their associated representations taken from a CNN for the filtering and the re-ranking steps. Moreover, we study the relevance of features from a finetuned network. In addition to that we explore the use of face detection, fisher vector and bag of visual words with those CNN features. We also test the impact of different similarity metrics. The results obtained are very promising.
Co-Authors Aïcha Sahel Imane Hachchane Yassine Ruichek