Wearable RGB Camera-based Navigation System for the Visually Impaired

Abobeah, Reham; Hussein, Mohamed E.; Abdelwahab, Moataz M.; Shoukry, Amin

doi:10.5220/0006617505550562

Cited by 8 publications

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“…The proposed model has been evaluated on three challenging datasets shown in Table 2, and briefly presented below. 1) Blind Navigation [55]: This dataset is composed of 12 pairs of variable-length videos that were captured by a user using a chest-mounted camera for various paths, half of them are taken indoor and the rest outdoor. Basically, these videos were manually annotated by some navigation instructions to guide the blind users along their routine paths; after defining their current locations w.r.t.…”

Section: The Proposed Approach Evaluation a Datasetsmentioning

confidence: 99%

Video Alignment Using Bi-Directional Attention Flow in a Multi-Stage Learning Model

Abobeah

Shoukry

Katto³

2020

IEEE Access

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Recently, deep learning techniques have contributed to solving a multitude of computer vision tasks. In this paper, we propose a deep-learning approach for video alignment, which involves finding the best correspondences between two overlapping videos. We formulate the video alignment task as a variant of the well-known machine comprehension (MC) task in natural language processing. While MC answers a question about a given paragraph, our technique determines the most relevant frame sequence in the context video to the query video. This is done by representing the individual frames of the two videos by highly discriminative and compact descriptors. Next, the descriptors are fed into a multi-stage network that is able, with the help of the bidirectional attention flow mechanism, to represent the context video at various granularity levels besides estimating the query-aware context part. The proposed model was trained on 10k video-pairs collected from ''YouTube''. The obtained results show that our model outperforms all known state of the art techniques by a considerable margin, confirming its efficacy. INDEX TERMS Bi-directional attention, temporal alignment, video retrieval, video synchronization, video alignment. REHAM ABOBEAH received the B.Sc. and M.Sc. degrees from the Computers and Systems Engineering Department, Faculty of Engineering, Al-Azhar University. She is currently pursuing the Ph.D. degree with the

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Section: The Proposed Approach Evaluation a Datasetsmentioning

confidence: 99%

Video Alignment Using Bi-Directional Attention Flow in a Multi-Stage Learning Model

Abobeah

Shoukry

Katto³

2020

IEEE Access

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“…Recently, many aid systems based on computer vision and image processing algorithms have been introduced and developed to meet the visually impaired and blind people's needs with scene understanding and interaction. However, most of the proposed aid systems, even traditional ones such as white canes and dog assistants, have been provided to facilitate navigation [1,2,3,4], obstacle avoidance, localisations, and grasping objects [5], without considering interactions with the surrounding people which represent a huge part of our daily activities. visually impaired and blind people needs to have an impression of human actions in order to be able to interact with them and get along with society.…”

Section: Introductionmentioning

confidence: 99%

Semantic Labeling of Human Action For Visually Impaired And Blind People Scene Interaction

Leyla¹,

Larabi²

2022

Preprint

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The aim of this work is to contribute to the development of a tactile device for visually impaired and blind persons in order to let them to understand actions of the surrounding people and to interact with them. First, based on the state-of-the-art methods of human action recognition from RGB − D sequences, we use the skeleton information provided by Kinect, with the disentangled and unified multi-scale Graph Convolutional (M S − G3D) model to recognize the performed actions. We tested this model on real scenes and found some of constraints and limitations. Next, we apply a fusion between skeleton modality with M S − G3D and depth modality with CNN in order to bypass the discussed limitations. Third, the recognized actions are labeled semantically and will be mapped into an output device perceivable by the touch sense.

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Survey and analysis of the current status of research in the field of outdoor navigation for the blind

Lian

Liu

2023

Disability and Rehabilitation: Assistive Technology

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Wearable RGB Camera-based Navigation System for the Visually Impaired

Cited by 8 publications

References 0 publications

Video Alignment Using Bi-Directional Attention Flow in a Multi-Stage Learning Model

Video Alignment Using Bi-Directional Attention Flow in a Multi-Stage Learning Model

Semantic Labeling of Human Action For Visually Impaired And Blind People Scene Interaction

Survey and analysis of the current status of research in the field of outdoor navigation for the blind

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