Snag Detection Robot for Visually Impaired Steering and Blind Individuals

Sowmiya, S.; Valarmathi, K.; Sathyavenkateshwaren, S.; Gobinath, M.; Thillaisivakavi, S.

doi:10.1109/icirca.2018.8597178

Cited by 5 publications

(5 citation statements)

References 6 publications

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“…If these two problems cannot be solved reasonably, the accuracy of video typical target motion trajectory prediction will be affected. In order to solve the abovementioned problems, this paper proposes a Social-LSTM-based algorithm for video target trajectory prediction [27]. e algorithm uses LSTM to process the temporal relationship between the same type target motion trajectory in different video frames.…”

Section: Video Target Trajectory Prediction Algorithm Incorporating Contextualmentioning

confidence: 99%

Application Research on Roller Skater Detection, Tracking, and Trajectory Prediction Based on Video Stream

Duan¹,

Meng²,

Ma³

et al. 2021

Scientific Programming

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With the continuous progress of science and technology, the sport of roller skating has developed rapidly and the technical level of the game has become higher and higher. Its sport performance has been rapidly improved. However, China’s roller skating is relatively late, and there is still a certain gap compared with many Western developed countries. In order to improve the performance of China’s roller skating, this study takes the representative Chinese and foreign excellent speed skaters as the research object and compares the sprinting technology of Chinese and foreign excellent speed skaters by using image measurement and image analysis to obtain the kinematic parameters and data of the athletes’ sprinting technology in the competition state. In view of the problem that the current video target tracking algorithm is easy to follow multiple targets, a video multiobject detection and tracking algorithm with improved tracking learning detection (TLD) is studied with the skater in the video as the research object. For the lost target, the prediction function of Kalman filter algorithm is used to track the trajectory of the typical target in the video, and the trajectory tracked by Kalman filter algorithm is used to compensate the lost part of TLD algorithm, so as to obtain the complete trajectory of the typical target in the video to improve the accuracy of video multiobject tracking. Since the existing trajectory prediction algorithms have the limitation of poor accuracy, a social-long short-term memory (Social-LSTM) network-based video typical target trajectory prediction algorithm is proposed to predict the trajectory sequences of typical targets to be detected by incorporating the contextual environment information and the interaction relationship between multiple target trajectories into the Social-LSTM network. The simulation results show that the proposed trajectory prediction algorithm outperforms the traditional LSTM algorithm, Hidden Markov Model Algorithm, and Hybrid Gaussian model algorithm, which is helpful to improve the accuracy of video roller skater target trajectory prediction, and the tracking success rate is 0.98.

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Section: Video Target Trajectory Prediction Algorithm Incorporating Contextualmentioning

confidence: 99%

Application Research on Roller Skater Detection, Tracking, and Trajectory Prediction Based on Video Stream

Duan¹,

Meng²,

Ma³

et al. 2021

Scientific Programming

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show abstract

“…Frequency Reference T1 11 articles [46], [106], [51], [97], [109], [27], [54], [110], [82], [55], [114] T2 25 articles [32], [29], [62], [24], [34], [73], [48], [50], [39], [94], [40], [95], [42], [78], [67], [31], [101], [37], [103], [85], [38], [111], [112], [113], [115] T3 18 articles [86], [87], [88], [90], [71], [64], [93], [35], [72], [74], [36], [96], [98], [69], …”

Section: Work Principlesmentioning

confidence: 99%

“…Sowmiya et al [55] expanded research on ultrasonic sensors to create a robot-based system for snag detection to assist visually impaired individuals. The system uses an ultrasonic sensor, infrared sensor, and a microcontroller-based robot for snag detection, showcasing the potential of microcontroller-based robots and sensor technology in offering navigation solutions for individuals with visual impairments.…”

Section: Work Principlesmentioning

confidence: 99%

“…Arduino is a popular open-source electronics platform used for building digital devices and interactive objects. It has been utilized to control various components of assistive systems, like motors, sensors, and display units [31,55,73,98,99]. Arduino is mentioned in one study:…”

Section: Arduinomentioning

confidence: 99%

“…• IEEE: 41 articles ( 40.6% of total) • Springer: 15 articles ( 14.8% of total) • ACM: 10 articles ( 9.9% of total) Deep Learning 63 articles [90], [106], [51], [97], [109], [81], [54], [110], [55], [114] Fig. 8: Publications made per functionality and working principles per year…”

Section: Other Smart Devicesmentioning

confidence: 99%

See 2 more Smart Citations

Intelligent Environments and Assistive Technologies For Assisting Visually Impairment People: A Systematic Literature Review

de Souza,

Francisco,

Tavares

et al. 2023

Preprint

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Intelligent Environments (IE) refer to fisical spaces imbued with pervasive and seamless intelligence, created to proactively support individuals in their daily routines. Developments in technologies such as the Internet of Things (IoT) and Artificial Intelligence (AI) have taken these environments from theoretical notions to practical realities. Simultaneously, the field of Ambient Assisted Living (AAL) has made significant strides. Evolving from Assistive Technology (AT), AAL represents an application of IE that specifically seeks to enable individuals —especially those with disabilities or the elderly— to lead healthier, more independent, and dignified lives through the assistance of technology integrated within their living environments. The confluence of IE and AAL has led to the rise of innovative solutions aimed at enhancing the lives of individuals with special needs,such as the Visually Impaired People (VIP). This research presents a systematic literature review investigating the utilization of IE, underpinned by AAL principles, in supporting VIPs. Initially, a pool of 14,760 studies was obtained from 9 databases, all published up to December 2022. After applying specific inclusion and exclusion criteria, this pool was reduced to 101 articles. Each of these articles was reviewed, analyzed, and categorized into four functional and operating principle categories to address five research questions. The study proposes multiple taxonomies as an approach to holistically synthesize the various technologies and devices categorized in the reviewed articles. Emerging research challenges and trends in this domain are highlighted, with a substantial trend being the escalating use of Deep Learning (DL) techniques. These techniques have been pivotal in the development of systems focused on object detection, path recognition, and navigation for devices, particularly smartphones, geared towards enhancing the lives of VIPs.

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Intelligent environments and assistive technologies for assisting visually impaired people: a systematic literature review

Souza,

Francisco,

Rosa Tavares

et al. 2024

Univ Access Inf Soc

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Snag Detection Robot for Visually Impaired Steering and Blind Individuals

Cited by 5 publications

References 6 publications

Application Research on Roller Skater Detection, Tracking, and Trajectory Prediction Based on Video Stream

Application Research on Roller Skater Detection, Tracking, and Trajectory Prediction Based on Video Stream

Intelligent Environments and Assistive Technologies For Assisting Visually Impairment People: A Systematic Literature Review

Intelligent environments and assistive technologies for assisting visually impaired people: a systematic literature review

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