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Papers/MagicEye: An Intelligent Wearable Towards Independent Livi...

MagicEye: An Intelligent Wearable Towards Independent Living of Visually Impaired

Sibi C. Sethuraman, Gaurav R. Tadkapally, Saraju P. Mohanty, Gautam Galada, Anitha Subramanian

2023-03-24Face RecognitionNavigateobject-detectionObject Detection
PaperPDFCode(official)

Abstract

Individuals with visual impairments often face a multitude of challenging obstacles in their daily lives. Vision impairment can severely impair a person's ability to work, navigate, and retain independence. This can result in educational limits, a higher risk of accidents, and a plethora of other issues. To address these challenges, we present MagicEye, a state-of-the-art intelligent wearable device designed to assist visually impaired individuals. MagicEye employs a custom-trained CNN-based object detection model, capable of recognizing a wide range of indoor and outdoor objects frequently encountered in daily life. With a total of 35 classes, the neural network employed by MagicEye has been specifically designed to achieve high levels of efficiency and precision in object detection. The device is also equipped with facial recognition and currency identification modules, providing invaluable assistance to the visually impaired. In addition, MagicEye features a GPS sensor for navigation, allowing users to move about with ease, as well as a proximity sensor for detecting nearby objects without physical contact. In summary, MagicEye is an innovative and highly advanced wearable device that has been designed to address the many challenges faced by individuals with visual impairments. It is equipped with state-of-the-art object detection and navigation capabilities that are tailored to the needs of the visually impaired, making it one of the most promising solutions to assist those who are struggling with visual impairments.

Results

TaskDatasetMetricValueModel
Facial Recognition and ModellingLFWAccuracy0.945OcularAI-Face
Facial Recognition and ModellingLFWF1-score0.9421OcularAI-Face
Facial Recognition and ModellingLFWPrecision0.9934OcularAI-Face
Facial Recognition and ModellingLFWRecall0.896OcularAI-Face
Face ReconstructionLFWAccuracy0.945OcularAI-Face
Face ReconstructionLFWF1-score0.9421OcularAI-Face
Face ReconstructionLFWPrecision0.9934OcularAI-Face
Face ReconstructionLFWRecall0.896OcularAI-Face
Face RecognitionLFWAccuracy0.945OcularAI-Face
Face RecognitionLFWF1-score0.9421OcularAI-Face
Face RecognitionLFWPrecision0.9934OcularAI-Face
Face RecognitionLFWRecall0.896OcularAI-Face
3DLFWAccuracy0.945OcularAI-Face
3DLFWF1-score0.9421OcularAI-Face
3DLFWPrecision0.9934OcularAI-Face
3DLFWRecall0.896OcularAI-Face
3D Face ModellingLFWAccuracy0.945OcularAI-Face
3D Face ModellingLFWF1-score0.9421OcularAI-Face
3D Face ModellingLFWPrecision0.9934OcularAI-Face
3D Face ModellingLFWRecall0.896OcularAI-Face
3D Face ReconstructionLFWAccuracy0.945OcularAI-Face
3D Face ReconstructionLFWF1-score0.9421OcularAI-Face
3D Face ReconstructionLFWPrecision0.9934OcularAI-Face
3D Face ReconstructionLFWRecall0.896OcularAI-Face

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