Crosswalk navigation for people with visual impairments on a wearable device

Cheng, Ruiqi; Wang, Kaiwei; Yang, Kailun; Long, Ningbo; Hu, Weijian; Chen, Hao; Bai, Jian; Liu, Dong

doi:10.1117/1.jei.26.5.053025

Cited by 29 publications

(13 citation statements)

References 23 publications

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“…But it holds a high computational complexity. Huang Xin et al [11] presented an improved method of zebra crossing detection based on bipolarity, similar work in [16] [35]. Image blocks with different sizes, which are set artificially, are used in bipolarity segmentation to detect the areas of alternating black and white stripes.…”

Section: B Crosswalk Detectionmentioning

confidence: 99%

Dynamic Crosswalk Scene Understanding for the Visually Impaired

Tian

Zheng

Zou

et al. 2021

IEEE Trans. Neural Syst. Rehabil. Eng.

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Independent mobility poses a great challenge to the visually impaired individuals. This paper proposes a novel system to understand dynamic crosswalk scenes, which detects the key objects, such as crosswalk, vehicle, and pedestrian, and identifies pedestrian traffic light status. The indication of where and when to cross the road is provided to the visually impaired based on the crosswalk scene understanding. Our proposed system is implemented on a head-mounted mobile device (Sensin-gAI G1) equipped with an Intel RealSense camera and a cellphone, and provides surrounding scene information to visually impaired individuals through audio signal. To validate the performance of the proposed system, we propose a crosswalk scene understanding dataset which contains three sub-datasets: a pedestrian traffic light dataset with 7447 images, a dataset of key objects on the crossroad with 1006 images and a crosswalk dataset with 3336 images. Extensive experiments demonstrated that the proposed system was robust and outperformed the state-of-the-art approaches. The experiment conducted with the visually impaired subjects shows that the system is practical useful.

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Section: B Crosswalk Detectionmentioning

confidence: 99%

Dynamic Crosswalk Scene Understanding for the Visually Impaired

Tian

Zheng

Zou

et al. 2021

IEEE Trans. Neural Syst. Rehabil. Eng.

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“…Apart from the generic scene perception, we previously achieved assistive navigation at urban traffic intersections for visually impaired people [13]. The AECA (adaptive extraction and consistency analysis) algorithm detects the position and orientation of zebra crosswalks in real time [14]. The pedestrian crossing lights detection algorithm leverages candidate extraction, candidate recognition, and temporal-spatial analysis to implement robust performance in challenging scenarios [15].…”

Section: A Assistive Scene Recognitionmentioning

confidence: 99%

Unifying Visual Localization and Scene Recognition for People With Visual Impairment

et al. 2020

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With the development of computer vision and mobile computing, assistive navigation for people with visual impairment arouses the attention of research communities. As two key challenges of assistive navigation, ''Where am I?'' and ''What are the surroundings?'' are still to be resolved by taking advantage of visual information. In this paper, we leverage the prevailing compact network as the backbone to build a unified network featuring two branches that implement scene description and scene recognition separately. Based on the unified network, the proposed pipeline performs scene recognition and visual localization simultaneously in the scenario of assistive navigation. The visual localization pipeline involves image retrieval and sequence matching. In the experiments, different configurations of the proposed pipeline are tested on public datasets to search for the optimal parameters. Moreover, on the real-world datasets captured by the wearable assistive device, the proposed assistive navigation pipeline is proved to achieve satisfactory performance. On the challenging dataset, the top-5 precision of scene recognition is more than 80%, and the visual localization precision is over 60% under a recall of 60%. The related codes and datasets are open-source online at https://github.com/chengricky/ScenePlaceRecognition.

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“…The algorithms described in [28] and [33] are based on parallel lines that are extracted by Hough Transform. Cheng et al [8] extract the bright crosswalk stripes by adaptive thresholding. They address challenging scenarios, such as partial occlusion, low contrast and distant crosswalks, and different illuminations.…”

Section: Crosswalk Detectionmentioning

confidence: 99%

Camera-based On-Road Detections for the Visually Impaired

Jakob¹,

Tick²

2020

ACTA POLYTECH HUNG

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Herein, we research the possibilities of assisting visually impaired pedestrians moving in traffic situations by using camera-based detection of relevant objects in their immediate surroundings. Therefore, we use and adapt algorithms from the field of driver assistance. We present a road background segmentation based on watersheds, whose results are used as input for the presented crosswalk and lane detection algorithms. The crosswalk detection is based on the application of two 1D mean filters and the lane detection on local computations of the EDF (Edge Distribution Function). In our evaluation, the described algorithms achieved good hit rates of 99.87% (road segmentation), 98.64% (crosswalk detection), and 97.89% (lane detection).

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Crosswalk navigation for people with visual impairments on a wearable device

Cited by 29 publications

References 23 publications

Dynamic Crosswalk Scene Understanding for the Visually Impaired

Dynamic Crosswalk Scene Understanding for the Visually Impaired

Unifying Visual Localization and Scene Recognition for People With Visual Impairment

Camera-based On-Road Detections for the Visually Impaired

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