Eyedentify: Alumni Project

My neighbor, Mr. Didwania, has a 100% loss of vision. 

Every morning, I see his wife guiding him on a walk, whispering in his ear when my sister and I were around to say ‘hello.’ It constantly nagged me that Mr. Didwania had to be told who he was about to meet.

Hence, it spurred me to brainstorm some device to assist him and wear that on his walks. Upon discussing this with him, I realized that such a  device would greatly benefit him and his wife during social outings. 

Henceforth, I formulated the problem statement for this project: 

“To design a device to enable people who are blind to recognize who is around them without having them to ask many questions or having someone else describe their surroundings every time.” 

Device Idea:

The basic idea is a cap with a Raspberry Pi (RPI) 3B+ computer attached to it and a Raspberry Pi Camera at the front, Powered by a generic ‘powerbank’ in the user’s pocket.

The RPI would run a code in Python, which after recognizing a face from a database, would play a pre-recorded audio file with the associated name. Henceforth, I named it ‘EyeDentify.’ 

Working of the Device:

When a person who is blind is wearing the face recognition system enabled cap, the modular computer system (Raspberry Pi) of the face recognition system receives an input video frame captured by the camera. The input video frame may comprise a person’s face/facial features in front of the camera. After that, the modular computer detects the facial features in the received input. Subsequently, the modular computer system compares the facial feature detected in the received input video frame with one or more historic facial images stored in the memory of the modular computer system. When the facial feature is found in the memory on the comparison, the modular computer system sends the audio file with the name of the person that corresponds to the matched face to the amplifier (HXJ8002) and the speaker  (general purpose, 8 Ohm). When the face/facial feature is not found in the memory on the comparison, the modular computer system sends a default audio file with a sound indicating no matches to the amplifier and the speaker. In this way, the face recognition system enabled cap assists the person who is blind to identify the person in front of them.

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