9,036 research outputs found
AmIE: An Ambient Intelligent Environment for Assisted Living
In the modern world of technology Internet-of-things (IoT) systems strives to
provide an extensive interconnected and automated solutions for almost every
life aspect. This paper proposes an IoT context-aware system to present an
Ambient Intelligence (AmI) environment; such as an apartment, house, or a
building; to assist blind, visually-impaired, and elderly people. The proposed
system aims at providing an easy-to-utilize voice-controlled system to locate,
navigate and assist users indoors. The main purpose of the system is to provide
indoor positioning, assisted navigation, outside weather information, room
temperature, people availability, phone calls and emergency evacuation when
needed. The system enhances the user's awareness of the surrounding environment
by feeding them with relevant information through a wearable device to assist
them. In addition, the system is voice-controlled in both English and Arabic
languages and the information are displayed as audio messages in both
languages. The system design, implementation, and evaluation consider the
constraints in common types of premises in Kuwait and in challenges, such as
the training needed by the users. This paper presents cost-effective
implementation options by the adoption of a Raspberry Pi microcomputer,
Bluetooth Low Energy devices and an Android smart watch.Comment: 6 pages, 8 figures, 1 tabl
Using remote vision: The effects of video image frame rate on visual object recognition performance
This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.The process of using remote vision was simulated in order to determine the effects of video image frame rate on the performance in visual recognition of stationary environmental hazards in the dynamic video footage of the pedestrian travel environment. The recognition performance was assessed against two different video image frame rate variations: 25 and 2 fps. The assessment included a range of objective and subjective criteria. The obtained results show that the effects of the frame rate variations on the performance are statistically insignificant. This paper belongs to the process of development of a novel system for navigation of visually impaired pedestrians. The navigation system includes a remote vision facility, and the visual recognition of the environmental hazards by the sighted human guide is a basic activity in aiding the visually impaired user of the system in mobility
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
“Visory” Mobile Application for the Visually Impaired
Unquestionably, visual impairment severely affects the quality of life and has an impact on many daily activities of the visually impaired individuals. Visory is a mobile application that aims to assist the visually impaired individuals with visual support, through human and automated visual support. Mobile phones are a norm; thus, solutions need to be created to assist the visually impaired while lessening the chances of discrimination against these individuals. With the help of volunteers, who opt to spend their valuable time helping others, the visually impaired individuals are able to connect via video calling and inquire for visual assistance using their device camera. Visory is also equipped with three vision APIs to ease further the life of these individuals, which includes object detection, text, and image recognition. Considering the limited time and budget of the project, Agile methodology is utilized to ensure the successful development of each of the modules within the stipulated deadline. Wide range of extensive testing techniques ensured minimal crashes, and uncovered bugs rectified. Ultimately, the objectives of the project were achieved. However, there is still room for improvement that needs to be addressed in future development for further stability and performance
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Mobile assistive technologies for the visually impaired
There are around 285 million visually impaired people worldwide, and around 370,000 people are registered as blind or partially sighted in the UK. Ongoing advances in information technology (IT) are increasing the scope for IT-based mobile assistive technologies to facilitate the independence, safety, and improved quality of life of the visually impaired. Research is being directed at making mobile phones and other handheld devices accessible via our haptic (touch) and audio sensory channels. We review research and innovation within the field of mobile assistive technology for the visually impaired and, in so doing, highlight the need for successful collaboration between clinical expertise, computer science, and domain users to realize fully the potential benefits of such technologies. We initially reflect on research that has been conducted to make mobile phones more accessible to people with vision loss. We then discuss innovative assistive applications designed for the visually impaired that are either delivered via mainstream devices and can be used while in motion (e.g., mobile phones) or are embedded within an environment that may be in motion (e.g., public transport) or within which the user may be in motion (e.g., smart homes)
Deep Thermal Imaging: Proximate Material Type Recognition in the Wild through Deep Learning of Spatial Surface Temperature Patterns
We introduce Deep Thermal Imaging, a new approach for close-range automatic
recognition of materials to enhance the understanding of people and ubiquitous
technologies of their proximal environment. Our approach uses a low-cost mobile
thermal camera integrated into a smartphone to capture thermal textures. A deep
neural network classifies these textures into material types. This approach
works effectively without the need for ambient light sources or direct contact
with materials. Furthermore, the use of a deep learning network removes the
need to handcraft the set of features for different materials. We evaluated the
performance of the system by training it to recognise 32 material types in both
indoor and outdoor environments. Our approach produced recognition accuracies
above 98% in 14,860 images of 15 indoor materials and above 89% in 26,584
images of 17 outdoor materials. We conclude by discussing its potentials for
real-time use in HCI applications and future directions.Comment: Proceedings of the 2018 CHI Conference on Human Factors in Computing
System
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