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A novel deep facenet framework for real-time face detection based on deep learning model

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Abstract

Real-time face detection has many challenges, such as non-frontal faces, tiny faces, occlusions, and multifarious backgrounds. Real-time face detection can be done by using Convolutional Neural Network (CNN) models, which result in elevated performance but have a huge computation time. It needs to be implemented on high-end computational devices to produce more accurate face detection results for high resolution images. We proposed a light architecture based on CNN for deep learning-based feature extraction and detection of human faces. The challenges faced during real-time face detection, such as occlusions, different scales, different backgrounds, varying positions, lighting, and poses, are resolved, and faces are detected accurately using the proposed framework. The amount of computation required for real-time face detection is reduced. This light architecture consists of two modules: the backbone module is used to contract the input size of the image and extract the features; the detection module transforms the feature map between prediction layers and detects faces at various scales. In our architecture, we use mini-inception blocks that minimize the computation cost and are implemented using available low-end system configurations without the need for external hardware. The proposed model uses anchor boxes to predict bounding boxes using dimensional clusters. The model is trained and tested using images from the WIDER Face dataset, which has images of various challenging conditions. Finally, images with multiple faces detected are displayed as output. The proposed work shows an increased accuracy rate with reduced computation cost over state-of-the-art performance on the benchmark dataset.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Mepco Schlenk Engineering College, Sivakasi, Tamil Nadu, India

    B Lakshmanan, A Vaishnavi, R Ananthapriya & A K Aananthalakshmi

Authors
  1. B Lakshmanan
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  2. A Vaishnavi
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  3. R Ananthapriya
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  4. A K Aananthalakshmi
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Correspondence to B Lakshmanan.

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Lakshmanan, B., Vaishnavi, A., Ananthapriya, R. et al. A novel deep facenet framework for real-time face detection based on deep learning model. Sādhanā 48, 265 (2023). https://doi.org/10.1007/s12046-023-02329-3

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  • DOI: https://doi.org/10.1007/s12046-023-02329-3

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