A multimodal smartphone interface for active perception by visually impaired

The diffuse availability of mobile devices, such as smartphones and tablets, has the potential to bring substantial benefits to the people with sensory impairments. The solution proposed in this paper is part of an ongoing effort to create an accurate obstacle and hazard detector for the visually impaired, which is embedded in a hand-held device. In particular, it presents a proof of concept for a multimodal interface to control the orientation of a smartphone's camera, while being held by a person, using a combination of vocal messages, 3D sounds and vibrations. The solution, which is to be evaluated experimentally by users, will enable further research in the area of active vision with human-in-the-loop, with potential application to mobile assistive devices for indoor navigation of visually impaired people

Low-fi skin vision: A case study in rapid prototyping a sensory substitution system

We describe the design process we have used to develop a minimal, twenty vibration motor Tactile Vision Sensory Substitution (TVSS) system which enables blind-folded subjects to successfully track and bat a rolling ball and thereby experience 'skin vision'. We have employed a low-fi rapid prototyping approach to build this system and argue that this methodology is particularly effective for building embedded interactive systems. We support this argument in two ways. First, by drawing on theoretical insights from robotics, a discipline that also has to deal with the challenge of building complex embedded systems that interact with their environments; second, by using the development of our TVSS as a case study: describing the series of prototypes that led to our successful design and highlighting what we learnt at each stage

FingerReader: A Wearable Device to Explore Printed Text on the Go

Accessing printed text in a mobile context is a major challenge for the blind. A preliminary study with blind people reveals numerous difficulties with existing state-of-the-art technologies including problems with alignment, focus, accuracy, mobility and efficiency. In this paper, we present a finger-worn device, FingerReader, that assists blind users with reading printed text on the go. We introduce a novel computer vision algorithm for local-sequential text scanning that enables reading single lines, blocks of text or skimming the text with complementary, multimodal feedback. This system is implemented in a small finger-worn form factor, that enables a more manageable eyes-free operation with trivial setup. We offer findings from three studies performed to determine the usability of the FingerReader.SUTD-MIT International Design Centr

Review of Machine Vision-Based Electronic Travel Aids

Visual impaired people have navigation and mobility problems on the road. Up to now, many approaches have been conducted to help them navigate around using different sensing techniques. This paper reviews several machine vision- based Electronic Travel Aids (ETAs) and compares them with those using other sensing techniques. The functionalities of machine vision-based ETAs are classified from low-level image processing such as detecting the road regions and obstacles to high-level functionalities such as recognizing the digital tags and texts. In addition, the characteristics of the ETA systems for blind people are particularly discussed

Smart Computing and Sensing Technologies for Animal Welfare: A Systematic Review

Animals play a profoundly important and intricate role in our lives today. Dogs have been human companions for thousands of years, but they now work closely with us to assist the disabled, and in combat and search and rescue situations. Farm animals are a critical part of the global food supply chain, and there is increasing consumer interest in organically fed and humanely raised livestock, and how it impacts our health and environmental footprint. Wild animals are threatened with extinction by human induced factors, and shrinking and compromised habitat. This review sets the goal to systematically survey the existing literature in smart computing and sensing technologies for domestic, farm and wild animal welfare. We use the notion of \emph{animal welfare} in broad terms, to review the technologies for assessing whether animals are healthy, free of pain and suffering, and also positively stimulated in their environment. Also the notion of \emph{smart computing and sensing} is used in broad terms, to refer to computing and sensing systems that are not isolated but interconnected with communication networks, and capable of remote data collection, processing, exchange and analysis. We review smart technologies for domestic animals, indoor and outdoor animal farming, as well as animals in the wild and zoos. The findings of this review are expected to motivate future research and contribute to data, information and communication management as well as policy for animal welfare

FingerReader: A Wearable Device to Support Text Reading on the Go

Visually impaired people report numerous difficulties with accessing printed text using existing technology, including problems with alignment, focus, accuracy, mobility and efficiency. We present a finger worn device that assists the visually impaired with effectively and efficiently reading paper-printed text. We introduce a novel, local-sequential manner for scanning text which enables reading single lines, blocks of text or skimming the text for important sections while providing real-time auditory and tactile feedback. The design is motivated by preliminary studies with visually impaired people, and it is small-scale and mobile, which enables a more manageable operation with little setup

Development of a text reading system on video images

Since the early days of computer science researchers sought to devise a machine which could automatically read text to help people with visual impairments. The problem of extracting and recognising text on document images has been largely resolved, but reading text from images of natural scenes remains a challenge. Scene text can present uneven lighting, complex backgrounds or perspective and lens distortion; it usually appears as short sentences or isolated words and shows a very diverse set of typefaces. However, video sequences of natural scenes provide a temporal redundancy that can be exploited to compensate for some of these deficiencies. Here we present a complete end-to-end, real-time scene text reading system on video images based on perspective aware text tracking. The main contribution of this work is a system that automatically detects, recognises and tracks text in videos of natural scenes in real-time. The focus of our method is on large text found in outdoor environments, such as shop signs, street names and billboards. We introduce novel efficient techniques for text detection, text aggregation and text perspective estimation. Furthermore, we propose using a set of Unscented Kalman Filters (UKF) to maintain each text region¿s identity and to continuously track the homography transformation of the text into a fronto-parallel view, thereby being resilient to erratic camera motion and wide baseline changes in orientation. The orientation of each text line is estimated using a method that relies on the geometry of the characters themselves to estimate a rectifying homography. This is done irrespective of the view of the text over a large range of orientations. We also demonstrate a wearable head-mounted device for text reading that encases a camera for image acquisition and a pair of headphones for synthesized speech output. Our system is designed for continuous and unsupervised operation over long periods of time. It is completely automatic and features quick failure recovery and interactive text reading. It is also highly parallelised in order to maximize the usage of available processing power and to achieve real-time operation. We show comparative results that improve the current state-of-the-art when correcting perspective deformation of scene text. The end-to-end system performance is demonstrated on sequences recorded in outdoor scenarios. Finally, we also release a dataset of text tracking videos along with the annotated ground-truth of text regions