Abstract
This paper presents a real-time system designed for visually impaired to aid them in social interactions. This system implemented a facial recognition algorithm which when embedded in a wearable device helps to detect the known and unknown faces at any crowded location or gathering. Our aim is to build a fully functional portable assistant that can recognize known faces, objects as well as the text from books. This system acts as the third eye for the blind. The facial recognition algorithm explained in this paper is the initial step towards this approach. Building such a prototype is a very challenging task as the portable camera is subjected to blur images due to the motion of the object and noise in uncertain lighting conditions. So, this paper presents an approach which is resilient to any change in illumination and is trained to detect the faces from the database with high accuracy. The two-tier architecture followed in this approach first identifies presence of a person and then applying face recognition to detect its identity. The object detection part helps in differentiating objects like photo frames and posters from a person and thus, proves more reliable than a standard face recognition framework. A dataset of 1000 images are taken for each face to train the model and system achieves a detection accuracy of 93.2% at a very high frame rate.
R. Goyal and K. Kalra—Contributed equally to this work.
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Goyal, R., Kalra, K., Kumar, P., Kaur, S. (2018). Intelligent Face Recognition System for Visually Impaired. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 906. Springer, Singapore. https://doi.org/10.1007/978-981-13-1813-9_12
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