Developing a tool for the visually impaired people is not a recently emerged problem. But developing a computer aided tool is a still developing area. The aim of all these systems is to help the user in navigation without the help of a second person. There are several works using computer vision techniques. But there is no existing method that help to solve the all basic needs of blind person. This project presents a comprehensive scheme for reconstructing a three-dimensional (3D) model from a stereo camera via multi-view calibration. The depth information is useful so as to estimate the actual position of the target object. It is an essential parameter that can allow visualization from multiple perspectives. We provide an improved method for detecting objects and calculating the distance of these objects using stereo vision in real time. The stages involved include camera calibration, image rectifying, disparity calculation, and three dimensional reconstruction. Results show that objects located from 65cm up to 203cm are properly measured for their distances, with an average error of 3cm. The precision of the measurement also depends on the quality of the calibration.

The Indoor and outdoor Navigation Assistance System aims to provide blind or visually impaired individuals with comprehensive navigation support in indoor and outdoor environments

ALOHOMORA is a vision-based blind stick. It aims at providing the visually impaired people with an easyand handy object identification and navigation system. The model that we will be using for objectidentification has been trained on the images of famous objects/obstacles that can be encountered by a visually impaired person in everyday life. This information will act as the basis for the results given to the user. Also, the distance to the object/obstacle will be calculated using a sensor and accordingly theinformation will be used to inform the person about the range or distance at which the object is.Furthermore, the system needs a continuous power supply to for its operation. The program on themini-computer should always be running in order to provide satisfying results to the visually impaired person. There is more more to come in project ,until wait Technologies used- 1.SOFTWARE - Operating System - Ubuntu 16.04,NOOBS 2.1.0 (Raspbian Pixel) Language - Python3 Machine Learning Libraries - Tensorflow 0.12.0,0.12.0, Inception v3 2.HARDWARE- Raspberry Pi model 3B, Ultrasonic Sensor HC SR-04, Passive Speaker Buzzer

Blind Navigation based on Stereo Vision and Computer Vision Obstacle Detection (Smart India Hackathon'17)

Low cost Indoor navigation system for people who are blind

Android app, GPS with walking and transit mode, adapted for blinded people with a new navigation system

CollabAlly is a system that makes collaboration awareness in document editing accessible to blind users. CollabAlly extracts collaborator, comment, and text-change information and their context from a document and presents them in a dialog box to provide easy access and navigation.

Empowering independence through technology: Explore our integrated assistive system combining advanced object detection and blind navigation, designed to enhance accessibility for individuals with visual impairments. Navigating the world with confidence and precision.

A research-based system using stereo vision and YOLO object detection to assist visually impaired and blind individuals. Utilized computer vision and OpenCV for precise object detection and depth estimation, delivering real-time audio feedback for navigation

Blind navigation system

A smart navigation assistance system for blind people using YOLO11 computer vision, haptic feedback, text-to-speech, and AI-powered voice queries

New social distancing guidelines imposed during COVID-19 have made it extremely difficult for the bind to maintain their independence. The World Health Organization (WHO) estimates that 88% of the world's blind population is 50 years and older, making this demographic extremely vulnerable to COVID-19. Despite this alarming statistic, little has been done to help the visually impaired cope with this pandemic. The CAT-EYE, a low- cost wearable assistive technology in the form of a hat, solves this problem by assisting blind individuals with navigating in a pandemic-stricken world. The CAT-EYE consists of three systems that work together to inform a blind user about their surroundings: 1. Mask Detection: When individuals come within six-feet of the user, CAT-EYE detects their presence using a LIDAR sensor and communicates their general location through vibrotactile motors. 2. Proximity Sensing: When individuals within six feet of the user are not wearing a mask, the device beeps loudly. This system was built using computer vision for the first prototype and AI, 3. IoT, and the NVIDIA Jetson Nano for the second prototype. 3. Public Alert: The user has the option to broadcast an alert through a speaker on the hat. This alert will notify people in the user's surroundings about the presence of a blind individual. The CAT-EYE was tested by analyzing performance in the camera's field of vision from 90 to 135 degrees. Design iterations based on test results helped CAT-EYE achieve 87% accuracy. The results demonstrated the applicability of the proposed solution as a pandemic-navigation aid to the blind.

盲人导航系统，年代久远，部分代码丢失

A blind navigation system using OpenCV could utilize computer vision algorithms to interpret visual data from a camera feed and provide audio or haptic feedback to guide the user. Features such as object recognition and depth perception could enhance the system's accuracy and effectiveness.

Empowering independence through technology: Explore our integrated assistive system combining advanced object detection and blind navigation, designed to enhance accessibility for individuals with visual impairments. Navigating the world with confidence and precision.

Empowering independence through technology: Explore our integrated assistive system combining advanced object detection and blind navigation, designed to enhance accessibility for individuals with visual impairments. Navigating the world with confidence and precision.

Wearable indoor navigation system for blind people based on "iBeacon" :

The mapping and relocalization module of CityU's blind navigation system.

A special specs, few vibrators, pair of headset,and a computing device in hand. this is the future we expect for visually challenged people. Blind navigation system as name suggests is a system that assist blind in everyday life.

In this project we developed real-time object detection system for blind individuals using YOLO algorithm, providing auditory feedback and enhancing spatial awareness. Improved independent navigation for visually impaired users.

it is meticulously advancing the development of the Sidewalk Environment Detection System for Assistive NavigaTION (hereinafter referred to as SENSATION). The primary objective of this venture is to enhance the mobility capabilities of blind or visually impaired persons (BVIPs) by ensuring safer and more efficient navigation on pedestrian pathways.

Intel Global AI Award 2025. Matches Apple Depth Pro metric depth maps to YOLOv8 object detections to provide spatially aware system prompts powering an AI blind-navigation LLM. Connected to ESP32S3 smart glasses for real-time use via smart glasses.

The purpose of the study was to evaluate the accuracy of Augmented Reality Software Development Kit (SDK), **ARKit’s** *Ray-casting* as an approach to evaluate how far real-world objects are detected in an indoor environment. The aim was to explore the feasibility of combining *Cloud Computing* with **ARKit's** *SDK* for the purpose of obstacle avoidance and navigation for the blind using an **iOS** (*Apple* mobile operating system) mobile device.

We propose a smart walking stick system especially made keeping the elderly in mind. With age comes diminishing memory and many more problems that seek support for both balance and navigation- cognitive and motor functions are diminished. Science and technology always make human life easier. Our application is on the go solution. A smart walking system which helps them navigate through life! Additional perks are that it can monitor heart rate and send out alerts to the nearest hospital whilst also alarming the people around for additional help. It also helps them cross the roads in a better and much safer way. Reminders for taking medicines in time/ general reminders can also be provided. We understand that the elderly might even have a very weak sense of vision. Keeping that in mind, we will be constructing a microcontroller based automated software that can corroborate a blind person to detect obstacles in front of him immediately. We implement this using ad hoc networks.

A navigation system for the blind

Blind Navigation System

The project includes python code to alert the user when a person is in front of the IoT device through speech/sound using face detection.This IoT project aims to help blind people travel independently by using ultrasonic distance sensor and a camera.

Thesis title: Navigation Aiding System for Visually Impaired People

No description available

Senior Project