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.

Toward a Computer Vision-based Wayfinding Aid for Blind Persons to Access Unfamiliar Indoor Environments.

Accurate assessment of progress allows managers to make adjustments to minimise costs when deviations from the schedule occur. Current practices of predicting the performance of a construction team require inspections that are still mainly manual, time consuming and can contain errors. Improper understanding of the current status can lead to further errors and unsuitable adjustments by the managing team, leading to more delays and increased cost. The problem is amplified when inspections take place in interior environments where the tasks are more complex. Efficient progress monitoring systems can help automate progress inspections, reduce the risks of error, facilitate proper and timely corrective actions, and prevent deviations in terms of cost and schedule. This paper presents a literature synthesis and interpretation of the state-of-the-art progress monitoring methods in terms of (a) data acquisition, as in technologies that are used for capturing the as-built scenes, (b) information retrieval, as in extracting the information needed from the as-built data, (c) progress estimation, which includes the comparison between the as-built and as-planned model in order to define the progress status and (d) visualisation of the results. The methods reviewed were categorised in terms of the technology used and assessed in terms of utility, time efficiency, accuracy, level of automation, required preparation, training requirements, cost and mobility. The review concludes with a recommendation of the most appropriate technologies to use based on the type of activities, environment and the needs of the inspection.

A Review of Automated Construction Progress Monitoring and Inspection Methods

Doors are important landmarks for indoor mobile robot navigation. Most existing algorithms for door detection use range sensors or work in limited environments because of restricted assumptions about color, pose, or lighting. We present a vision-based door detection algorithm that achieves robustness by utilizing a variety of features, including color, texture, and intensity edges. We introduce two novel geometric features that increase performance significantly: concavity and bottom-edge intensity profile. The features are combined using Adaboost to ensure optimal linear weighting. On a large database of images collected in a wide variety of conditions, the algorithm achieves more than 90% detection with a low false positive rate. Additional experiments demonstrate the suitability of the algorithm for real-time applications using a mobile robot equipped with an off-the-shelf camera and laptop.

/pdf/visual-detection-of-lintel-occluded-doors-from-a-single-4978ali21x.pdf

Visual detection of lintel-occluded doors from a single image

On the use of Bayesian Networks to develop behaviours for mobile robots

http://amirsadeghi.persiangig.com/hamvoroodi/papers/A%20robot%20team%20for%20surveillance%20tasks%20Design%20and%20architecture.pdf

A robot team for surveillance tasks: Design and architecture

A mobile robot, called a ranger, equipped with a ring of sonars and a color camera is at the center of this research effort. The ranger is part of a fleet of heterogenous robots. Its task is to quickly deploy multiple smaller robots with specialized sensing capabilities, called scouts, into different rooms. In order to achieve the goal, the ranger must be able to safely navigate through potentially unknown urban environments as well as autonomously detect areas into which the scouts should be released. This paper presents the ranger's sensing and control algorithms and reports results from several different environments.

Real-time door detection in cluttered environments

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Real-time door detection in cluttered environments