A Spot Reminder System for the Visually Impaired Based on a Smartphone Camera

The present paper proposes a smartphone-camera-based system to assist visually impaired users in recalling their memories related to important locations, called spots, that they visited. The memories are recorded as voice memos, which can be played back when the users return to the spots. Spot-to-spot correspondence is determined by image matching based on the scale invariant feature transform. The main contribution of the proposed system is to allow visually impaired users to associate arbitrary voice memos with arbitrary spots. The users do not need any special devices or systems except smartphones and do not need to remember the spots where the voice memos were recorded. In addition, the proposed system can identify spots in environments that are inaccessible to the global positioning system. The proposed system has been evaluated by two experiments: image matching tests and a user study. The experimental results suggested the effectiveness of the system to help visually impaired individuals, including blind individuals, recall information about regularly-visited spots

OMap: An assistive solution for identifying and localizing objects in a semi-structured environment

A system capable of detection and localization of objects of interest in a semi-structured environment will enhance the quality of life of people who are blind or visually impaired. Towards building such a system, this thesis presents a personalized real-time system called O\u27Map that finds misplaced/moved personal items and localizes them with respect to known landmarks. First, we adopted a participatory design approach to identify users’ need and functionalities of the system. Second, we used the concept from system thinking and design thinking to develop a real-time object recognition engine that was optimized to run on low form factor devices. The object recognition engine finds robust correspondences between the query image and item templates using K-D tree of invariant feature descriptor with two nearest neighbors and ratio test. Quantitative evaluation demonstrates that O\u27Map identifies object of interest with an average F-measure of 0.9650

A Navigation System for the Visually Impaired: A Fusion of Vision and Depth Sensor

For a number of years, scientists have been trying to develop aids that can make visually impaired people more independent and aware of their surroundings. Computer-based automatic navigation tools are one example of this, motivated by the increasing miniaturization of electronics and the improvement in processing power and sensing capabilities. This paper presents a complete navigation system based on low cost and physically unobtrusive sensors such as a camera and an infrared sensor. The system is based around corners and depth values from Kinect’s infrared sensor. Obstacles are found in images from a camera using corner detection, while input from the depth sensor provides the corresponding distance. The combination is both efficient and robust. The system not only identifies hurdles but also suggests a safe path (if available) to the left or right side and tells the user to stop, move left, or move right. The system has been tested in real time by both blindfolded and blind people at different indoor and outdoor locations, demonstrating that it operates adequately.</jats:p

Fine-Grained Product Class Recognition for Assisted Shopping

Assistive solutions for a better shopping experience can improve the quality of life of people, in particular also of visually impaired shoppers. We present a system that visually recognizes the fine-grained product classes of items on a shopping list, in shelves images taken with a smartphone in a grocery store. Our system consists of three components: (a) We automatically recognize useful text on product packaging, e.g., product name and brand, and build a mapping of words to product classes based on the large-scale GroceryProducts dataset. When the user populates the shopping list, we automatically infer the product class of each entered word. (b) We perform fine-grained product class recognition when the user is facing a shelf. We discover discriminative patches on product packaging to differentiate between visually similar product classes and to increase the robustness against continuous changes in product design. (c) We continuously improve the recognition accuracy through active learning. Our experiments show the robustness of the proposed method against cross-domain challenges, and the scalability to an increasing number of products with minimal re-training.Comment: Accepted at ICCV Workshop on Assistive Computer Vision and Robotics (ICCV-ACVR) 201

Vision-based Assistive Indoor Localization

An indoor localization system is of significant importance to the visually impaired in their daily lives by helping them localize themselves and further navigate an indoor environment. In this thesis, a vision-based indoor localization solution is proposed and studied with algorithms and their implementations by maximizing the usage of the visual information surrounding the users for an optimal localization from multiple stages. The contributions of the work include the following: (1) Novel combinations of a daily-used smart phone with a low-cost lens (GoPano) are used to provide an economic, portable, and robust indoor localization service for visually impaired people. (2) New omnidirectional features (omni-features) extracted from 360 degrees field-of-view images are proposed to represent visual landmarks of indoor positions, and then used as on-line query keys when a user asks for localization services. (3) A scalable and light-weight computation and storage solution is implemented by transferring big database storage and computational heavy querying procedure to the cloud. (4) Real-time query performance of 14 fps is achieved with a Wi-Fi connection by identifying and implementing both data and task parallelism using many-core NVIDIA GPUs. (5) Rene localization via 2D-to-3D and 3D-to-3D geometric matching and automatic path planning for efficient environmental modeling by utilizing architecture AutoCAD floor plans. This dissertation first provides a description of assistive indoor localization problem with its detailed connotations as well as overall methodology. Then related work in indoor localization and automatic path planning for environmental modeling is surveyed. After that, the framework of omnidirectional-vision-based indoor assistive localization is introduced. This is followed by multiple refine localization strategies such as 2D-to-3D and 3D-to-3D geometric matching approaches. Finally, conclusions and a few promising future research directions are provided

The SmartVision navigation prototype for the blind

The goal of the project "SmartVision: active vision for the blind" is to develop a small and portable but intelligent and reliable system for assisting the blind and visually impaired while navigating autonomously, both outdoor and indoor. In this paper we present an overview of the prototype, design issues, and its different modules which integrate a GIS with GPS, Wi-Fi, RFID tags and computer vision. The prototype addresses global navigation by following known landmarks, local navigation with path tracking and obstacle avoidance, and object recognition. The system does not replace the white cane, but extends it beyond its reach. The user-friendly interface consists of a 4-button hand-held box, a vibration actuator in the handle of the cane, and speech synthesis. A future version may also employ active RFID tags for marking navigation landmarks, and speech recognition may complement speech synthesis

Navigation framework using visual landmarks and a GIS

In an unfamiliar environment we spot and explore all available information which might guide us to a desired location. This largely unconscious processing is done by our trained sensory and cognitive systems. These recognise and memorise sets of landmarks which allow us to create a mental map of the environment, and this map enables us to navigate by exploiting very few but the most important landmarks stored in our memory. In this paper we present a route planning, localisation and navigation system which works in real time. It integrates a geographic information system of a building with visual landmarks for localising the user and for validating the navigation route. Although designed for visually impaired persons, the system can also be employed to assist or transport persons with reduced mobility in way finding in a complex building. © 2013 The Authors. Published by Elsevier B.V