Three-dimensional (3D) imaging has recently been applied to human gesture recognition using depth maps from RGB-D sensors. An alternative which has been scarcely explored is 3D Integral Imaging, which has shown to give very competitive results in object reconstruction and recognition tasks, even under challenging conditions (e.g. low illumination, occlusions). Integral Imaging has some remarkable advantages over other sensors that may give 3D information (like RGB-D sensors). One of the most important ones is its long range working capability, which stands out even more when compared against other sensors that lose their capabilities for depths of 2m or more. In this paper we present results corresponding to the application of the integral imaging 3D acquisition technique for the recognition of human gestures, when there are occlusions that may hinder the recognition capability. We also present results comparing its capability against that given by an RGB-D sensor (Kinect) and that obtained when only one of the cameras in the camera array is used. Our results show that Integral Imaging compares more or less similarly to Kinect and the monocular case when there are not occlusions, but much more favorably when there are. We also show that the camera spatial resolution may be an issue to account for, when we refer to gesture recognition under occlusions, for the monocular case, but it is less sensitive for the Integral Imaging case, because the features that are extracted from Integral Imaging seem to be more descriptive and discriminative than for the monocular counterpart case.
KEYWORDS: Visualization, Mid-IR, 3D image processing, Integral imaging, Photon counting, Infrared sensors, Sensors, Cameras, Signal to noise ratio, Sensing systems, Image processing, 3D displays, Wavelets
In this paper, we present an overview of our previously published work on the application of the maximum likelihood (ML) reconstruction method to integral images acquired with a mid-wave infrared detector on two different types of scenes: one of them consisting of a road, a group of trees and a vehicle just behind one of the trees (being the car at a distance of more than 200m from the camera), and another one consisting of a view of the Wright Air Force Base airfield, with several hangars and different other types of installations (including warehouses) at distances ranging from 600m to more than 2km. Dark current noise is considered taking into account the particular features this type of sensors have. Results show that this methodology allows to improve visualization in the photon counting domain.
KEYWORDS: Integral imaging, 3D image processing, Cameras, Video, Gesture recognition, 3D image reconstruction, Visualization, 3D acquisition, 3D displays, Image resolution
In this keynote address paper, we present an overview of our previously published work on the application of pattern recognition techniques and integral imaging for human gesture recognition.
KEYWORDS: Integral imaging, Cameras, Imaging systems, 3D image processing, 3D acquisition, Compressed sensing, Sensors, Digital holography, Optical filters, Stereoscopy
In this keynote address paper, we present an overview of our previously published work on using compressive sensing in multi-dimensional imaging. We shall examine a variety of multi dimensional imaging approaches and applications, including 3D multi modal imaging integrated with polarimetric and multi spectral imaging, integral imaging and digital holography. This Keynote Address paper is an overview of our previously reported work on 3D imaging with compressive sensing.
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