object detection for visually impaired

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object detection for visually impaired

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object detection for visually impaired

2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops. ; Al-Shehri, W.S.

Echolocation [. Redmon, J.; Farhadi, A. YOLO-v3: An incremental improvement.

Accurate Image Super-Resolution Using Very Deep Convolutional Networks.

These kinds of devices are accurate in terms of location, but are ineffective in case of obstacle avoidance and object identification.

Various rehabilitation workers and teachers working in this field were also involved to help to conduct the experiments smoothly. prior to publication. You must have JavaScript enabled in your browser to utilize the functionality of this website. Circuits Syst.

It has an omnidirectional wheel assisted with a high-speed processing controller using a LAM-based linearization system with a non-linear disturbance observer.

detection visually stereoscopic algorithm impaired obstacle aid navigation based system contours represented fig results ; Braithwaite, T.; Cicinelli, M.V. ; Goodale, M.A. [. Then, the YOLO-v3 model is trained with the generated dataset either through transfer learning or with direct training. Distance vision impairment is classified into mild, moderate, severe, and blindness based on visual acuteness, when it is worse than 6/12, 6/18, 6/60, and 3/60, respectively [, Apart from medical treatment, people use various aids for rehabilitation, education, social inclusion, or work.

It runs at the highest measured floating-point operation speed, which indicates that the network is more successful when applying GPU resources [. Refreshable braille displays, screen magnifiers, and screen readers are also used to obtain information while using computer or mobile systems.

The main contribution of the proposed work is to design an artificial intelligent fully automated assistive technique for visually impaired people to perceive the objects in the surrounding and provide obstacle-aware navigation, where auditory inputs are given to users in real-time. Kim, J.; Lee, J.K.; Lee, K.M. endobj Thus, if there is a currency detection mode in the device, that mode must have a higher object detection threshold value than other modes to avoid such ambiguity. In Proceedings of the 2009 Workshop on Applications of Computer Vision (WACV), Snowbird, UT, USA, 78 December 2009; pp.

Once the images were annotated, the respective annotation files were also generated.

The higher the processor, the greater the number of frames per seconds that can be processed.

The proposed system can work universally in the existing infrastructure which has been used before by visually impaired people. We use cookies to help provide and enhance our service and tailor content and ads. Yang, X.; Yuan, S.; Tian, Y. Assistive Clothing Pattern Recognition for Visually Impaired People. Abdul Kalam Technical University, Lucknow 226031, India, Institute for Technological Development and Innovation in Communications (IDeTIC), University of Las Palmas de Gran Canaria (ULPGC), 35017 Las Palmas de G.C., Spain. Croce, D.; Giarre, L.; Pascucci, F.; Tinnirello, I.; Galioto, G.E. Intuitive Tactile Zooming for Graphics Accessed by Individuals Who are Blind and Visually Impaired. Copyright 2022 Elsevier B.V. or its licensors or contributors. Neural Correlates of Natural Human Echolocation in Early and Late Blind Echolocation Experts. 65176525. [.

Deep Multi-Layer Perceptron-Based Obstacle Classification Method from Partial Visual Information: Application to the Assistance of Visually Impaired People. They experienced lots of problems while using the stick in crowed areas. The auditory information that is conveyed to the user after scene segmentation and obstacle identification is optimized to obtain more information in less time for faster processing of video frames. To develop a system that can identify indoor and outdoor objects, notify the users, and send all information to a remote server repeatedly at a fixed time interval. impaired vibrotactile avoidance haptic <>/ExtGState<>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/MediaBox[ 0 0 595.32 841.92] /Contents 4 0 R/Group<>/Tabs/S/StructParents 0>>

View 2 excerpts, references background and methods. People also make use of GPS-equipped assistive devices, which help with navigation and orientation for a particular position. A white cane is used by visually impaired people around the world.

Outdoor mode also has an image enlarge function, so that far objects can be detected early. Jarraya, S.K. JavaScript seems to be disabled in your browser. B-Tech Electronics and Communication Engineering, Amal Jyothi College of Engineering, Kanjirappally, Kerala, India, https://doi.org/10.1088/1757-899X/1085/1/012006.

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Citation Therese Yamuna Mahesh et al 2021 IOP Conf.

Centre for Advanced Studies, Dr. A.P.J. Rastogi, R.; Pawluk, T.V.D.

Frame processing time in blind assistive devices is different for a normal human and visually impaired persons.

A system to identify products in their everyday routine by this system consists of a camera, a speaker and an image processing system that tries to detect the object and transform that object into the audio form and inform blind person about those objects.

1085 012006, 1 Associate Professor, Dept. ; Ali, M.S.

However, the effective utilization of sensor-based technologies and computer vision could result in a highly efficient and supportive device, to make them aware of the surroundings. Due to this, weight adjustment takes less time compared to the case when training the dataset for the first time.

If an object is detected in the captured image frame, equivalent audio is played after the detection of an object to convey information to the user. First, all audio files for the name of objects label are optimized such that there is no silence in recording, except the space in between two words. You seem to have javascript disabled.

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The proposed system can easily differentiate between obstacles and known objects. In Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 26 June1 July 2016; pp.

4 0 obj The time complexity is low, allowing a user to perceive the surrounding scene in real time. BibTeX

published in the various research areas of the journal.

This site uses cookies. The testing accuracy and processing time for a single image frame are given in, Information optimization is performed to get more information in a shorter time duration.

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Available online: Thaler, L.; Arnott, S.R. Sign up for newsletter today. Publishing. those of the individual authors and contributors and not of the publisher and the editor(s).

The indoor mode has a smaller threshold value for the distance of obstacle compared to the outdoor mode. Then, real-time object detection is carried out by using YOLO network.

However, guide dogs are unable to give directions in complex cases. By continuing to use this site you agree to our use of cookies. The results demonstrate 95.19% object detection accuracy and 99.69% object recognition accuracy in real-time. With the use of the proposed methodology, users can interpret more about the things going around and receive obstacle-aware navigation as well. A YOLO (You look only once) algorithm is used in our project. [.

However, these tactile marks vanish after some time, and then it is not easy for a blind person to differentiate between banknotes.

The transfer learning method requires a pre-trained model and it will be beneficial when a similar dataset is already trained over this model and respective generated trained model files will be used for transfer learning. [, Lin, T.-Y.

Kang, M.-C.; Chae, S.-H.; Sun, J.-Y. The rest of the paper is organized as follows: First, the methodology is explored in, In this section, the whole process is explained to provide navigation assistance to visually impaired people, which consists of the preparation and pre-processing of the dataset, augmentation, annotation and dataset training on the deep-learning model. Output information optimization was further performed to increase the robustness of the system. Currency notes also feature the tactile marks with raised dots to allow the person to identify the banknote. ; Flaxman, S.R.

This paper represents an IoT-enabled automated object recognition system that simplifies the mobility problems of the visually impaired in indoor and outdoor environments. This problem is not discussed in many research articles where such work is conducted. The remaining 500 images from each training class were divided into a ratio of 7:3 for training and validation set, respectively.

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Visually impaired people face numerous difficulties in their daily life, and technological interventions may assist them to meet these challenges.

The visually impaired people previously used blind sticks, which give alerts for objects coming in front of the stick by means of vibrations. Chang, W.-J. Lpez-De-Ipia, D.; Lorido, T.; Lpez, U. BlindShopping: Enabling Accessible Shopping for Visually Impaired People through Mobile Technologies.

If a user wants to record image frames, which came across the device, it can be stored in subsequent frames. The system is made for hundred objects of different classes. Goyal, S.; Bhavsar, S.; Patel, S.; Chattopadhyay, C.; Bhatnagar, G. SUGAMAN: Describing floor plans for visually impaired by annotation learning and proximity-based grammar.

Bourne, R.R.A. and C.M.T.-G. All authors have read and agreed to the published version of the manuscript. In Proceedings of the 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Francisco, CA, USA, 1318 June 2010; pp. 18. Vision impairment is one of the major health problems in the world. ScienceDirect is a registered trademark of Elsevier B.V. ScienceDirect is a registered trademark of Elsevier B.V. IoT Enabled Automated Object Recognition for the Visually Impaired. Object Detection Featuring 3D Audio Localization for Microsoft HoloLensA Deep Learning based Sensor Substitution Approach for the Blind. A novel obstacle detection method based on deformable grid for the visually impaired.

In Proceedings of the 2018 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 35 April 2018; pp. and C.M.T.-G.; supervision, M.K.D.

The overall accuracy of the proposed system in object detection and recognition is 99.31% and 98.43% respectively. A camera-based assistive system for visually impaired or blind persons to read text from signage and objects that are held in the hand and then communicate this information aurally, which outperforms previous algorithms on some measures. Calik, R.C.

The confusion matrix is prepared for a threshold of 0.5; because of this, if the captured image is not proper, there may be chances that image shows some similarity with other banknotes along with the actual currency note. IEEE Trans.

10331038. Face recognizer can also be associated with the device, where users can identify known persons and family members, which will help in them to be social and secure.

While in outdoor environments, trained objects such as cars, humans, and vehicles were used.

The Raspberry Pi camera module takes the image and transfers it to the Raspberry Pi desktop.

Aladrn, A.; Lopez-Nicolas, G.; Puig, L.; Guerrero, J.J. Navigation Assistance for the Visually Impaired Using RGB-D Sensor with Range Expansion. Before the trials, all those involved were briefly informed about the device so that users were aware about the experimentation steps.

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These people can use this particular prototype for self -navigating their way. %PDF-1.7 Ando, B.; Baglio, S.; Marletta, V.; Valastro, A. [, Parikh, N.; Shah, I.; Vahora, S. Android Smartphone Based Visual Object Recognition for Visually Impaired Using Deep Learning. This paper proposes an artificial intelligence-based fully automatic assistive technology to recognize different objects, and auditory inputs are provided to the user in real time, which gives better understanding to the visually impaired person about their surroundings.

This type of Darknet-53 is used as a feature extractor in YOLO-v3 that is composed of 53 convolutional layers. As weight adjustment and loss in each convolving layer reduce in a shorter time, the transfer learning method can also be used to retrain the dataset when the training got abrupt due to any reasons.

An algorithm enabling blind users to find and read barcodes. All were given sticks and a supporting person while using the proposed framework. Various challenges are faced by visually impaired patients even in the familiar environment. If none of the trained objects are detected in the captured frame, then it will calculate the distance through the ultrasonic sensors. More sensors will be associated with it to detect, for example, downstairs and other trajectories, giving a wider range of assistance to the visually impaired. In near vision impairment, vision is poorer than M.08 or N6, even after correction. The performance of the proposed device has been tested on 36 people, including 20 visually impaired and 16 blind-folded people belonging to different age groups. The detected image is converted to speech by using the gTTS module and the audio result is provided to the user through a headset. A computer vision-based indoor wayfinding system for assisting blind people to independently access unfamiliar buildings by incorporating door detection with text recognition and extracting and recognizing the text information associated with the detected objects.

Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

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Recognition-by-components: a theory of human image understanding. In Proceedings of the 2018 IEEE Intelligent Vehicles Symposium (IV), Changshu, China, 2630 June 2018; pp. [, Tekin, E.; Coughlan, J.M. Takatori, N.; Nojima, K.; Matsumoto, M.; Yanashima, K.; Magatani, K. Development of voice navigation system for the visually impaired by using IC tags. [. [, Deng, J.; Dong, W.; Socher, R.; Li, L.-J.

Training images are augmented and manually annotated to bring more robustness to the trained model. Real-time objects in an image are detected with their names represented on a bounding box and these names are converted to speech signals. Object Detection and Translation for Blind People Using Deep Learning, Rapid object detection using a boosted cascade of simple features, Robust and Effective Component-Based Banknote Recognition for the Blind, Recognizing clothes patterns for blind people by confidence margin based feature combination, Assistive Text Reading from Complex Background for Blind Persons, Bipolarity and Projective Invariant-Based Zebra-Crossing Detection for the Visually Impaired, Context-based indoor object detection as an aid to blind persons accessing unfamiliar environments, Visual saliency as an aid to updating digital maps, Wearable Mobility Aid for Low Vision Using Scene Classification in a Markov Random Field Model Framework.

It can also easily differentiate between objects and obstacles coming in front of the camera.

When the calculated distance through the ultrasonic sensor is below the threshold value, the device makes an acoustic warning or vibrates, but it can be irritating for a visually impaired person who is standing in a crowd and repeatedly listening same prompt or continuous vibrations.

Chen, X.; Xu, J.; Yu, Z.

The statements, opinions and data contained in the journals are solely ; Winn, J.; Zisserman, A. Deep learning-based object detection, in assistance with various distance sensors, is used to make the user aware of obstacles, to provide safe navigation where all information is provided to the user in the form of audio.

Third is the case in which a number of multiple objects of various categories are present in the captured scene, which can require a considerably longer time to convey audio information to the user. The developed technology is found to be highly useful, with which users can also understand the surrounding scenario easily while navigating without putting in too much effort. The proposed system uses Single Shot Detector (SSD) model with MobileNet and Tensorflow-lite to recognize objects along with the currency note in the real-time scenario in both indoor and outdoor environments. The information about the images, such as the size of the image, size, and position of the bounding box or bounding boxes (in case of multiple instances or multiple objects in the same image), were recorded and saved into the .xml format. Fall Detection and Prevention Control Using Walking-Aid Cane Robot.

Di, P.; Hasegawa, Y.; Nakagawa, S.; Sekiyama, K.; Fukuda, T.; Huang, J.; Huang, Q.

The accuracy of the proposed system in object detection and recognition is 99.31% and 98.43% respectively. The authors declare no conflict of interest.

In Proceedings of the 9th International Conference on Smart Homes and Health Telematics, Montreal, QC, Canada, 2022 June 2011; LNCS 6719. pp. Confusion matrix is another parameter that can be utilized to check the performance of object detection and recognition on a set of test data whose true values are known. To find out more, see our, Browse more than 100 science journal titles, Read the very best research published in IOP journals, Read open access proceedings from science conferences worldwide, Published under licence by IOP Publishing Ltd, Bundesanstalt fr Materialforschung und prfung (BAM), IOP Conference Series: Materials Science and Engineering, Fast and accurate obstacle detection of manipulator in complex humanmachine interaction workspace, Traffic vehicle cognition in severe weather based on radar and infrared thermal camera fusion, In object detection deep learning methods, YOLO shows supremum to Mask R-CNN, M-YOLO: A Nighttime Vehicle Detection Method Combining Mobilenet v2 and YOLO v3, Non-contact measurement of human respiration using an infrared thermal camera and the deep learning method, Detection and Content Retrieval of Object in an Image using YOLO, Head of Division "Thermographic Methods" (m/f/d), 13 positions for PhD candidates/research associates, Copyright 2022 IOP

Help us to further improve by taking part in this short 5 minute survey, Identification of Denatured Biological Tissues Based on Compressed Sensing and Improved Multiscale Dispersion Entropy during HIFU Treatment, Convolutional Neural Network Approach for Multispectral Facial Presentation Attack Detection in Automated Border Control Systems, Variational Information Bottleneck for Semi-Supervised Classification, Conditional Adversarial Domain Adaptation Neural Network for Motor Imagery EEG Decoding, Entropy on Biosignals and Intelligent Systems II, https://www.who.int/blindness/causes/trends/en/, https://www.who.int/news-room/fact-sheets/detail/blindness-andvisual-impairment, http://creativecommons.org/licenses/by/4.0/, Object Detection in single frame with GPU, Object Detection in single frame in single board DSP processor without GPU, Average time of Audio for count of object, Average time of Audio for name of object with count, Mobile Kinect, laptop Electrode matrix, headphone and RF transmitter, Detect obstacle and generate audio warning, Depth camera, glasses, CPU, headphone and ultrasonic sensor, Depth Camera on Smart glass, Laptop, and headphone, Obstacle Recognition and generate clarinet sound as warning, Obstacle recognition and vibration feedback for the direction, Object detection with direction of object into audio output, Localization of the person in the building, RGB Camera, Distance Sensor, DSP processor, Headphone, Local dataset of highly relevant objects for VIP, Object detection, Count of objects, obstacle warnings, read text, and works in different modes. Annual International Conference on Emerging Research Areas on "COMPUTING & COMMUNICATION SYSTEMS FOR A FOURTH INDUSTRIAL REVOLUTION" (AICERA 2020) 14th-16th December 2020, Kanjirapally, India Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Four laser sensors are used in the system to detect the objects in the direction of the front, left, right and ground. In Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA, 2126 July 2017; pp. By clicking accept or continuing to use the site, you agree to the terms outlined in our.

; Garlisi, D.; Valvo, A.L. The proposed system assists the visually impaired to recognize objects which the visually impaired cannot identify generally. As it does not depend on a computer language interpreter, instructions can also be made for local dialect or language for which proper recordings are not yet available.

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The Pascal Visual Object Classes (VOC) Challenge.

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Product was successfully added to your shopping cart. Redmon, J.; Farhadi, A. YOLO9000: Better, Faster, Stronger. Everingham, M.; Van Gool, L.; Williams, C.K.I. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

Braille helps a visually impaired or blind person to obtain information, but it is limited to people who have knowledge of it.

and S.Y., writingreview and editing, M.K.D. This issue can be easily eliminated by increasing the threshold value or by considering only the highest label prediction probability. As the similarity in banknotes is greater, confusion matrix for currency notes is shown in. A novel camera-based computer vision technology to automatically recognize banknotes to assist visually impaired people and employs the spatial relationship of matched SURF features to detect if there is a bill in the camera view, which largely alleviates false recognition. All articles published by MDPI are made immediately available worldwide under an open access license. These frames can also help to construct a proper dataset and to approach the challenging scenario, which can be dealt with to develop much more robust devices. Design and Construction of Electronic Aid for Visually Impaired People.

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Blind or visually impaired people does not have any conscious about the danger they are facing in their daily life. Visit our dedicated information section to learn more about MDPI. Various augmentation techniques, such as rotation at different angles, skewing, mirroring, flipping, brightness levels, noise levels, and a combination of these techniques, was used to enrich the dataset to many folds, shown in. Qiu, X.; Yuan, C. Improving Object Detection with Convolutional Neural Network via Iterative Mechanism. Images of objects that are highly relevant in the lives of the visually challenged are trained using deep learning neural networks. endobj ; Boon, N.L.

It takes a lot of mental effort and attention when walking only with the help of a stick.

; Leasher, J.; Limburg, H.; et al.

Resources are used in an optimized way to reduce energy consumption.

Information in braille characters can be installed in most places, but it is not practical to install it everywhere and convey full information.

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Ahmad, N.S. In Proceedings of the 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA), Aqaba, Jordan, 28 October1 November 2018; pp. ; Yoo, J.-W.; Ko, S.-J. <>

The statements, opinions and data contained in the journal, 1996-2022 MDPI (Basel, Switzerland) unless otherwise stated. To keep doing their daily tasks, vision-impaired people usually seek help from others. x=F|:GZoE _&z& I#'n5xWuMW..?^n9i~qe=cq_EW6mWo^?Qq(xIH7(`2YIpNL_'WMOIQM/Nl.^I5i< n=e#p'{7W.'7=v38|@&Cp"4\ 5ON=y#L]D~u}=rdxL:=1s ?8fN3DN H %"|-Ji9'wLt/zE*G=wp"zw2rlf{wUu|4_

The proposed system assists the visually impaired to recognize several objects and provides an audio message to aware the user. The model is also trained to perform banknote detection and recognition to help in daily business transaction-related activities along with other object detection and navigation assistance for visually impaired people.

: Mater. So, one of the objectives of the proposed system is to differentiate between trained objects and obstacles.

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Visually impaired individuals are at drawback due to lack of. Thus, even though the machine learning model processes the frames in real-time, it takes a lot of time to process the next frame, as it has a dependency on the number of the objects present in the current frame and the length of the name of object.

; Oliva, A.; Torralba, A.

; Romera, E.; Cheng, R.; Chen, T.; Wang, K. Unifying terrain awareness through real-time semantic segmentation.

Once all objects were detected, the text label was converted into speech, or a respective audio label recording was played, and subsequently, the next frame was processed.

420425. The 8-megapixel camera used can capture images of 3280 2464 pixels with a fixed focus lens. Thus, the time taken to prompt person five times is reduced to 5 person. 12. Thus, the information transmission time will increase with an increase in the number of the objects in current image frame and cause a delay to processing the next frame. Results for different object classes in different scenarios are shown below in, Different approaches for object classification and object detection were also tested in given datasets, such as VGG-16, VGG-19 and Alexnet. You are accessing a machine-readable page.

; Demirci, M.F.

Loss function for YOLO architecture is given by Equation (2). The average accuracy of this proposed method is 95.19% and 99.69% for object detection and recognition, respectively. For example, a car at far distance can be easily detected when enlarged, because after enlarging the image, the number of pixels is increased, and it becomes an easy task to detect that car. CVPR 2001. Regarding input signal observation, 98% responded that they have heard the sound appropriately and the remaining 2% of individuals missed hearing the signal. Get all the latest information on Events, Sales and Offers. The proposed system is developed with the least cost components such that the whole system costs an affordable budget.

Augmentation and manual annotation are performed on the dataset to make the system robust and free from overfitting. For

This proof of concept system can handle clothes in deficient color without any pattern, as well as clothing with multiple colors and complex patterns to aid both blind and color deficient people. ; Maire, M.; Belongie, S.; Hays, J.; Perona, P.; Ramanan, D.; Dollr, P.; Zitnick, C.L. ; Ketchum, J.M. Future work will focus on the inclusion of more objects in the dataset, which can make the dataset more efficient for the assistance of visually impaired people. Semantic Scholar is a free, AI-powered research tool for scientific literature, based at the Allen Institute for AI. In Proceedings of the 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, San Diego, CA, USA, 28 August1 September 2012; pp. In Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, 2730 June 2016; pp. In total, 650 images of each class were collected and, out of those, 150 images were kept separated for the testing set. In the training neural network, the predictions were made through the following Equations (3)(6): Once the CNN was trained with the dataset, the final trained model was equipped in the object detection framework. A live video feed was associated to the framework and image frames were subsequently captured. Hoang, V.-N.; Nguyen, T.-H.; Le, T.-L.; Tran, T.-H.; Vuong, T.-P.; Vuillerme, N. Obstacle detection and warning system for visually impaired people based on electrode matrix and mobile Kinect.