Recognition of elevators with the Kinect cane system for the visually impaired

Kuramochi, Yusuke; Takizawa, Hotaka; Aoyagi, Mayumi; Ezaki, Nobuo; Mizuno, Shinji

doi:10.1109/sii.2014.7028024

Cited by 4 publications

(4 citation statements)

References 6 publications

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“…The Kinect cane system can also recognize upward staircases, downward staircases, and elevators on the basis of the recognition results of planes. The recognition methods are described in detail, for example, in [68,70], and, in this section, the recognition results are shown in Figures 10-12.…”

Section: Other Objectsmentioning

confidence: 99%

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Assistive Systems for the Visually Impaired Based on Image Processing

Takizawa¹,

Aoyagi²

2018

Causes and Coping With Visual Impairment and Blindness

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In this chapter, we proposed three assistive systems for visually impaired individuals based on image processing: Kinect cane system, Kinect goggle system, and light checking system. The Kinect cane system can detect obstacles of various sizes and also recognize objects such as seats. A visually impaired user is notified of the results of detection and recognition by means of vibration feedback. The Kinect goggle system is another type of wearable system, and can make user's hands free. The light checking system is implemented as an application for a smartphone, and can tell a visually impaired user the ON/OFF states of room lights and elevator button lights. The experimental results demonstrate that the proposed systems are effective in helping visually impaired individuals in everyday environments.

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Section: Other Objectsmentioning

confidence: 99%

“…a) and (b) shows an example scene and its depth data, respectively. Planes are recognized[70] by using the following method based on random sample consensus (RANSAC) algorithm[71]:…”

mentioning

confidence: 99%

Assistive Systems for the Visually Impaired Based on Image Processing

Takizawa¹,

Aoyagi²

2018

Causes and Coping With Visual Impairment and Blindness

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“…Vision-based assistants, such as monocular cameras, stereoscopic cameras, and Red, Green, Blue, and Depth (RGB-D) cameras, have been widely used for target finding, localization, navigation, etc. For example, an important function of vision-based applications is to help visually impaired users find specific objects to use, such as chairs [9], sign patterns in road environments, markers posted on podiums and classroom doors [10], up/down stairways [11] [12] [13] [14], and elevators [15]. For other applications, like visual simultaneous localization and mapping (VSLAM) for blind navigation has become a popular research field [16] [17] [18] [19] as well.…”

Section: Introductionmentioning

confidence: 99%

A Wearable Device for Indoor Imminent Danger Detection and Avoidance With Region-Based Ground Segmentation

Song

Clark

et al. 2020

IEEE Access

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Avoiding objects independently in indoor environments for individuals with severe visual impairment is one of the significant challenges in daily life. This paper presents a wearable application to help visually impaired people quickly build situational awareness and traverse safely. The system utilizes Red, Green, Blue, and Depth (RGB-D) camera and an Inertial Measurement Unit (IMU) to detect objects and the collision-free path in real-time. A region proposal module is presented to decide where to identify the ground from 3D point clouds. The segmented ground area can act as the traversable path, and its corresponding region in the image is removed to prevent detecting painted objects. The system can provide information about the category, distance, and direction of the detected objects by fusing the depth image and the neural network results. A 3D acoustic feedback mechanism is designed to improve the situational awareness for visually impaired people, and guild them traverse safely. The advantage of this system is that our 3D region proposal module can robustly propose the potential ground region and greatly reduce the computation cost of the ground segmentation. Besides, a typical machine-learning-based approach may miss objects because they could not be recognized, though they still may pose a danger. Another advantage of our approach is that the imminent danger detector can detect such unrecognizable objects to help users avoid a collision. Finally, experimental results demonstrate that the proposed system can be a useful indoor assistant tool to help blind individuals with collision avoidance and wayfinding.INDEX TERMS Convolutional neural network, ground segmentation, object detection, point cloud, region of interest, visual impairment, wearable assistive system.

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“…Sensor-based systems have been developed to recognize color blocks [ 57 ], benches [ 58 ], tables [ 59 ], staircases [ 60 , 61 , 62 , 63 ], and elevators [ 64 ], using laser range sensors [ 62 , 63 ], laser pointers combined with a CCD camera [ 61 ], or Kinect sensors [ 57 , 58 , 59 , 64 ]. These systems allow visually impaired users to find and use target objects.…”

Section: Introductionmentioning

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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Recognition of elevators with the Kinect cane system for the visually impaired

Cited by 4 publications

References 6 publications

Assistive Systems for the Visually Impaired Based on Image Processing

Assistive Systems for the Visually Impaired Based on Image Processing

A Wearable Device for Indoor Imminent Danger Detection and Avoidance With Region-Based Ground Segmentation

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

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