A Spot Navigation System for the Visually Impaired by Use of SIFT-Based Image Matching

Takizawa, Hotaka; Orita, Kazunori; Aoyagi, Mayumi; Ezaki, Nobuo; Mizuno, Shinji

doi:10.1007/978-3-319-20687-5_16

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…It is difficult for the visually impaired user to set a camera direction in the playback mode so that the frames overlap sufficiently, and therefore it is likely that the image matching would fail. Our previous navigation system [ 72 ] and the VizMap localization system, proposed by Gleason et al [ 73 ], used single scene images for spot identification and therefore had the same difficulty in image matching. In contrast, if a panoramic image is produced from multiple scene images with the help of a sighted assistant and is used for the image matching, it would be more promising as shown in Figure 3 b.…”

Section: Outline Of the Spot Reminder Systemmentioning

confidence: 99%

A Spot Reminder System for the Visually Impaired Based on a Smartphone Camera

Takizawa

Orita

Aoyagi

et al. 2017

Sensors

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The present paper proposes a smartphone-camera-based system to assist visually impaired users in recalling their memories related to important locations, called spots, that they visited. The memories are recorded as voice memos, which can be played back when the users return to the spots. Spot-to-spot correspondence is determined by image matching based on the scale invariant feature transform. The main contribution of the proposed system is to allow visually impaired users to associate arbitrary voice memos with arbitrary spots. The users do not need any special devices or systems except smartphones and do not need to remember the spots where the voice memos were recorded. In addition, the proposed system can identify spots in environments that are inaccessible to the global positioning system. The proposed system has been evaluated by two experiments: image matching tests and a user study. The experimental results suggested the effectiveness of the system to help visually impaired individuals, including blind individuals, recall information about regularly-visited spots.

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Section: Outline Of the Spot Reminder Systemmentioning

confidence: 99%

A Spot Reminder System for the Visually Impaired Based on a Smartphone Camera

Takizawa

Orita

Aoyagi

et al. 2017

Sensors

Self Cite

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Event Venue Navigation for Visually Impaired People

Watanabe

Minagawa

2019

2019 IEEE International Conference on Big Data and Smart Computing (BigComp)

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A CNN-SIFT Hybrid Pedestrian Navigation Method Based on First-Person Vision

et al. 2018

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Abstract:The emergence of new wearable technologies, such as action cameras and smart glasses, has driven the use of the first-person perspective in computer applications. This field is now attracting the attention and investment of researchers aiming to develop methods to process first-person vision (FPV) video. The current approaches present particular combinations of different image features and quantitative methods to accomplish specific objectives, such as object detection, activity recognition, user-machine interaction, etc. FPV-based navigation is necessary in some special areas, where Global Position System (GPS) or other radio-wave strength methods are blocked, and is especially helpful for visually impaired people. In this paper, we propose a hybrid structure with a convolutional neural network (CNN) and local image features to achieve FPV pedestrian navigation. A novel end-to-end trainable global pooling operator, called AlphaMEX, has been designed to improve the scene classification accuracy of CNNs. A scale-invariant feature transform (SIFT)-based tracking algorithm is employed for movement estimation and trajectory tracking of the person through each frame of FPV images. Experimental results demonstrate the effectiveness of the proposed method. The top-1 error rate of the proposed AlphaMEX-ResNet outperforms the original ResNet (k = 12) by 1.7% on the ImageNet dataset. The CNN-SIFT hybrid pedestrian navigation system reaches 0.57 m average absolute error, which is an adequate accuracy for pedestrian navigation. Both positions and movements can be well estimated by the proposed pedestrian navigation algorithm with a single wearable camera.

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A Spot Navigation System for the Visually Impaired by Use of SIFT-Based Image Matching

Cited by 3 publications

References 8 publications

A Spot Reminder System for the Visually Impaired Based on a Smartphone Camera

A Spot Reminder System for the Visually Impaired Based on a Smartphone Camera

Event Venue Navigation for Visually Impaired People

A CNN-SIFT Hybrid Pedestrian Navigation Method Based on First-Person Vision

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