Unfamiliar Indoor Environments Research Articles

Toward a computer vision-based wayfinding aid for blind persons to access unfamiliar indoor environments

Independent travel is a well known challenge for blind and visually impaired persons. In this paper, we propose a proof-of-concept computer vision-based wayfinding aid for blind people to independently access unfamiliar indoor environments. In order to find different rooms (e.g. an office, a lab, or a bathroom) and other building amenities (e.g. an exit or an elevator), we incorporate object detection with text recognition. First we develop a robust and efficient algorithm to detect doors, elevators, and cabinets based on their general geometric shape, by combining edges and corners. The algorithm is general enough to handle large intra-class variations of objects with different appearances among different indoor environments, as well as small inter-class differences between different objects such as doors and door-like cabinets. Next, in order to distinguish intra-class objects (e.g. an office door from a bathroom door), we extract and recognize text information associated with the detected objects. For text recognition, we first extract text regions from signs with multiple colors and possibly complex backgrounds, and then apply character localization and topological analysis to filter out background interference. The extracted text is recognized using off-the-shelf optical character recognition (OCR) software products. The object type, orientation, location, and text information are presented to the blind traveler as speech.

A Hybrid Positioning System for Indoor Navigation on Mobile Phones using Panoramic Images

In this paper, we propose a novel positioning system for indoor navigation which helps a user navigate easily to desired destinations in an unfamiliar indoor environment using his mobile phone. The system requires only the user`s mobile phone with its basic equipped sensors such as a camera and a compass. The system tracks user`s positions and orientations using a vision-based approach that utilizes 360° panoramic images captured in the environment. To improve the robustness of the vision-based method, we exploit a digital compass that is widely installed on modern mobile phones. This hybrid solution outperforms existing mobile phone positioning methods by reducing the error of position estimation to around 0.7 meters. In addition, to enable the proposed system working independently on mobile phone without the requirement of additional hardware or external infrastructure, we employ a modified version of a fast and robust feature matching scheme using Histogrammed Intensity Patch. The experiments show that the proposed positioning system achieves good performance while running on a mobile phone with a responding time of around 1 second.

Individual- and Gender-Related Differences in Indoor Wayfinding

The current study used a variety of behavioral and self-report measures to examine gender differences in way finding behavior following incidental leaming in an unfamiliar indoor environment. College students were led along a circuitous route and then asked to find their way back to the start. Choice of route back, comments made during the task, directional accuracy, and self-report after the task indicated three relatively efficient patterns of way finding and a distinctly inefficient pattern, characterized by frequent back-trailing, poor directional accuracy, and uncertainty about the task. Gender differences showed a discrepancy between measures of way finding efficiency and directional accuracy. Although there was no gender difference in choice of route back, men were significantly more accurate than women in locating the direction of the destination. Also, women reported significantly more uncertainty about carrying out the task.