Human gesture recognition using three-dimensional integral imaging

Traver, Vicente; Carmona, Pedro; Salvador-Balaguer, Eva; Pla, Filiberto; Javidi, Bahram

doi:10.1364/josaa.31.002312

Cited by 33 publications

(4 citation statements)

References 40 publications

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“…Results showed that integral imaging using an array of cameras outperformed RGB-D sensing and single image capture particularly in challenging partial occlusion conditions (Fig. 9) [83,84]. Integral imaging provides a variety of potential features that are very adequate for application scenarios where challenging conditions, such as partial occlusion, cannot be overcome by other 3D sensing technologies.…”

Section: Hand Gesture Recognition Using a 3d Sensing Approach Based Omentioning

confidence: 99%

“…Integral imaging is a powerful alternative to RGB-D sensors, due to its passive sensing nature and the fact that it can work under certain challenging limitations such as partial occlusion and low illumination conditions. This section summarizes part of the previous research work on 3D sensing for gesture recognition based on integral imaging [83,84]. These works showed the capabilities of integral imaging for hand gesture recognition using 3D image reconstruction techniques that overcome active RGB-D sensors in challenging partial occlusion scenarios.…”

Section: Hand Gesture Recognition Using a 3d Sensing Approach Based Omentioning

confidence: 99%

“…The hand gesture motion is characterized by means of a Bag of Words (BoW) method from previously extracted Spatiotemporal Interest Points (STIPs). These feature points are characterized by extracting local features around the STIPS, which are used to build the BoW characterization that is eventually used in a Support Vector Machine (SVM) classifier [83,84]. Experiments were carried out using a 3x3 camera array for the elemental image acquisition.…”

Section: Hand Gesture Recognition Using a 3d Sensing Approach Based Omentioning

confidence: 99%

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Roadmap on 3D integral imaging: sensing, processing, and display

et al. 2020

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This Roadmap article on three-dimensional integral imaging provides an overview of some of the research activities in the field of integral imaging. The article discusses various aspects of the field including sensing of 3D scenes, processing of captured information, and 3D display and visualization of information. The paper consists of a series of 15 sections from the experts presenting various aspects of the field on sensing, processing, displays, augmented reality, microscopy, object recognition, and other applications. Each section represents the vision of its author to describe the progress, potential, vision, and challenging issues in this field.

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Section: Hand Gesture Recognition Using a 3d Sensing Approach Based Omentioning

confidence: 99%

Section: Hand Gesture Recognition Using a 3d Sensing Approach Based Omentioning

confidence: 99%

Section: Hand Gesture Recognition Using a 3d Sensing Approach Based Omentioning

confidence: 99%

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Roadmap on 3D integral imaging: sensing, processing, and display

et al. 2020

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“…Integral 3-D imaging is used in a wide range of applications, such as 3-D movie displays, 2,3 extraction and tracking of objects, 4,5 conversion of images into holograms, [6][7][8] refocusing, [9][10][11][12][13] and user interfaces. 14 In the display stage of the integral 3-D method, a 3-D image is generated using a lens array to reconstruct light rays. These light rays are equivalent to the light rays emitted from the subject in the capturing stage.…”

Section: Introductionmentioning

confidence: 99%

Capturing method for integral three-dimensional imaging using multiviewpoint robotic cameras

et al. 2018

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Integral three-dimensional (3-D) technology for next-generation 3-D television must be able to capture dynamic moving subjects with pan, tilt, and zoom camerawork as good as in current TV program production. We propose a capturing method for integral 3-D imaging using multiviewpoint robotic cameras. The cameras are controlled through a cooperative synchronous system composed of a master camera controlled by a camera operator and other reference cameras that are utilized for 3-D reconstruction. When the operator captures a subject using the master camera, the region reproduced by the integral 3-D display is regulated in real space according to the subject's position and view angle of the master camera. Using the cooperative control function, the reference cameras can capture images at the narrowest view angle that does not lose any part of the object region, thereby maximizing the resolution of the image. 3-D models are reconstructed by estimating the depth from complementary multiviewpoint images captured by robotic cameras arranged in a two-dimensional array. The model is converted into elemental images to generate the integral 3-D images. In experiments, we reconstructed integral 3-D images of karate players and confirmed that the proposed method satisfied the above requirements.

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High‐resolution and compact virtual mouse using lens arrays to capture finger images on light sensors

Qin

Chang

et al. 2017

J Soc Info Display

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To realize a finger positioning device, as called “virtual mouse,” to replace a touchpad, touchscreen, or even real mouse, current positioning technologies cannot achieve a sufficient resolution, a compact volume, and a simple detection algorithm simultaneously. For this problem, using a light‐emitting diode source, two lens arrays, and two light sensors, we design and implement a virtual mouse prototype. The optical architecture is carefully determined for a compact volume, a sufficient resolution, and a high detection accuracy. Corresponding to a compact system volume of 3.1 mm (thickness) × 4.5 mm (length) × 2, a theoretical resolution higher than 25 pixels per inch (ppi) can be obtained over a working area of 10 cm × 10 cm. Experiments are also implemented, in which a mean detection error of 0.24 cm that corresponds to approximately two distinguishable points, and a minimal resolution of 26 ppi over the whole working area are verified. If the system thickness is relaxed to 25 mm, a resolution higher than 200 ppi can be achieved. The proposed virtual mouse, which is simple enough and potential to be extended for three‐dimensional position detection, can be integrated with a flat panel display to achieve a compact display application that can interact with users.

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Human gesture recognition using three-dimensional integral imaging

Cited by 33 publications

References 40 publications

Roadmap on 3D integral imaging: sensing, processing, and display

Roadmap on 3D integral imaging: sensing, processing, and display

Capturing method for integral three-dimensional imaging using multiviewpoint robotic cameras

High‐resolution and compact virtual mouse using lens arrays to capture finger images on light sensors

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