The Experts below are selected from a list of 14151 Experts worldwide ranked by ideXlab platform
Narciso Garcia - One of the best experts on this subject based on the ideXlab platform.
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A real-time gesture recognition system using near-Infrared Imagery.
PloS one, 2019Co-Authors: Tomas Mantecon, Carlos R. Del-blanco, Fernando Jaureguizar, Narciso GarciaAbstract:Visual hand gesture recognition systems are promising technologies for Human Computer Interaction, as they allow a more immersive and intuitive interaction. Most of these systems are based on the analysis of skeleton information, which is in turn inferred from color, depth, or near-Infrared Imagery. However, the robust extraction of skeleton information from images is only possible for a subset of hand poses, which restricts the range of gestures that can be recognized. In this paper, a real-time hand gesture recognition system based on a near-Infrared device is presented, which directly analyzes the Infrared Imagery to infer static and dynamic gestures, without using skeleton information. Thus, a much wider range of hand gestures can be recognized in comparison with skeleton-based approaches. To validate the proposed system, a new dataset of near-Infrared Imagery has been created, from which good results that outperform other state-of-the-art strategies have been obtained.
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hand gesture recognition using Infrared Imagery provided by leap motion controller
Advanced Concepts for Intelligent Vision Systems, 2016Co-Authors: Tomas Mantecon, Fernando Jaureguizar, Carlos R Delblanco, Narciso GarciaAbstract:Hand gestures are one of the main alternatives for Human-Computer Interaction. For this reason, a hand gesture recognition system using near-Infrared Imagery acquired by a Leap Motion sensor is proposed. The recognition system directly characterizes the hand gesture by computing a global image descriptor, called Depth Spatiograms of Quantized Patterns, without any hand segmentation stage. To deal with the high dimensionality of the image descriptor, a Compressive Sensing framework is applied, obtaining a manageable image feature vector that almost preserves the original information. Finally, the resulting reduced image descriptors are analyzed by a set of Support Vectors Machines to identify the performed gesture independently of the precise hand location in the image. Promising results have been achieved using a new hand-based near-Infrared database.
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ACIVS - Hand Gesture Recognition Using Infrared Imagery Provided by Leap Motion Controller
Advanced Concepts for Intelligent Vision Systems, 2016Co-Authors: Tomas Mantecon, Carlos R. Del-blanco, Fernando Jaureguizar, Narciso GarciaAbstract:Hand gestures are one of the main alternatives for Human-Computer Interaction. For this reason, a hand gesture recognition system using near-Infrared Imagery acquired by a Leap Motion sensor is proposed. The recognition system directly characterizes the hand gesture by computing a global image descriptor, called Depth Spatiograms of Quantized Patterns, without any hand segmentation stage. To deal with the high dimensionality of the image descriptor, a Compressive Sensing framework is applied, obtaining a manageable image feature vector that almost preserves the original information. Finally, the resulting reduced image descriptors are analyzed by a set of Support Vectors Machines to identify the performed gesture independently of the precise hand location in the image. Promising results have been achieved using a new hand-based near-Infrared database.
Tomas Mantecon - One of the best experts on this subject based on the ideXlab platform.
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A real-time gesture recognition system using near-Infrared Imagery.
PloS one, 2019Co-Authors: Tomas Mantecon, Carlos R. Del-blanco, Fernando Jaureguizar, Narciso GarciaAbstract:Visual hand gesture recognition systems are promising technologies for Human Computer Interaction, as they allow a more immersive and intuitive interaction. Most of these systems are based on the analysis of skeleton information, which is in turn inferred from color, depth, or near-Infrared Imagery. However, the robust extraction of skeleton information from images is only possible for a subset of hand poses, which restricts the range of gestures that can be recognized. In this paper, a real-time hand gesture recognition system based on a near-Infrared device is presented, which directly analyzes the Infrared Imagery to infer static and dynamic gestures, without using skeleton information. Thus, a much wider range of hand gestures can be recognized in comparison with skeleton-based approaches. To validate the proposed system, a new dataset of near-Infrared Imagery has been created, from which good results that outperform other state-of-the-art strategies have been obtained.
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hand gesture recognition using Infrared Imagery provided by leap motion controller
Advanced Concepts for Intelligent Vision Systems, 2016Co-Authors: Tomas Mantecon, Fernando Jaureguizar, Carlos R Delblanco, Narciso GarciaAbstract:Hand gestures are one of the main alternatives for Human-Computer Interaction. For this reason, a hand gesture recognition system using near-Infrared Imagery acquired by a Leap Motion sensor is proposed. The recognition system directly characterizes the hand gesture by computing a global image descriptor, called Depth Spatiograms of Quantized Patterns, without any hand segmentation stage. To deal with the high dimensionality of the image descriptor, a Compressive Sensing framework is applied, obtaining a manageable image feature vector that almost preserves the original information. Finally, the resulting reduced image descriptors are analyzed by a set of Support Vectors Machines to identify the performed gesture independently of the precise hand location in the image. Promising results have been achieved using a new hand-based near-Infrared database.
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ACIVS - Hand Gesture Recognition Using Infrared Imagery Provided by Leap Motion Controller
Advanced Concepts for Intelligent Vision Systems, 2016Co-Authors: Tomas Mantecon, Carlos R. Del-blanco, Fernando Jaureguizar, Narciso GarciaAbstract:Hand gestures are one of the main alternatives for Human-Computer Interaction. For this reason, a hand gesture recognition system using near-Infrared Imagery acquired by a Leap Motion sensor is proposed. The recognition system directly characterizes the hand gesture by computing a global image descriptor, called Depth Spatiograms of Quantized Patterns, without any hand segmentation stage. To deal with the high dimensionality of the image descriptor, a Compressive Sensing framework is applied, obtaining a manageable image feature vector that almost preserves the original information. Finally, the resulting reduced image descriptors are analyzed by a set of Support Vectors Machines to identify the performed gesture independently of the precise hand location in the image. Promising results have been achieved using a new hand-based near-Infrared database.
Bir Bhanu - One of the best experts on this subject based on the ideXlab platform.
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Activity and individual human recognition in Infrared Imagery
Behavioral Biometrics for Human Identification: Intelligent Applications, 2009Co-Authors: Bir Bhanu, J. HanAbstract:In this chapter, we investigate repetitive human activity patterns and individual recognition in thermal Infrared Imagery, where human motion can be easily detected from the background regardless of the lighting conditions and colors of the human clothing and surfaces, and backgrounds. We employ an efficient spatiotemporal representation for human repetitive activity and individual recognition, which represents human motion sequence in a single image while preserving spatiotemporal characteristics. A statistical approach is used to extract features for activity and individual recognition. Experimental results show that the proposed approach achieves good performance for repetitive human activity and individual recognition. © 2010, IGI Global.
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Human Activity Recognition in Thermal Infrared Imagery
CVPR, 2005Co-Authors: J. Han, Bir BhanuAbstract:In this paper, we investigate human repetitive activity properties\nfrom thermal Infrared Imagery, where human motion can be easily detected\nfrom the background regardless of lighting conditions and colors\nof the human surfaces and backgrounds. We employ an efficient spatiotemporal\nrepresentation for human repetitive activity recognition, which represents\nhuman motion sequence in a single image while preserving some temporal\ninformation. A statistical approach is used to extract features for\nactivity recognition. Experimental results show that the proposed\napproach achieves good performance for human repetitive activity\nrecognition.
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CVPR Workshops - Human Activity Recognition in Thermal Infrared Imagery
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops, 1Co-Authors: J. Han, Bir BhanuAbstract:In this paper, we investigate human repetitive activity properties from thermal Infrared Imagery, where human motion can be easily detected from the background regardless of lighting conditions and colors of the human surfaces and backgrounds. We employ an efficient spatiotemporal representation for human repetitive activity recognition, which represents human motion sequence in a single image while preserving some temporal information. A statistical approach is used to extract features for activity recognition. Experimental results show that the proposed approach achieves good performance for human repetitive activity recognition.
Andrew T Jessup - One of the best experts on this subject based on the ideXlab platform.
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land based Infrared Imagery for marine mammal detection
Remote Sensing and Modeling of Ecosystems for Sustainability VIII, 2011Co-Authors: Joseph Graber, Jim Thomson, Brian Polagye, Andrew T JessupAbstract:A land-based Infrared (IR) camera is used to detect endangered Southern Resident killer whales in Puget Sound, Washington, USA. The observations are motivated by a proposed tidal energy pilot project, which will be required to monitor for environmental effects. Potential monitoring methods also include visual observation, passive acoustics, and active acoustics. The effectiveness of observations in the Infrared spectrum is compared to observations in the visible spectrum to assess the viability of Infrared Imagery for cetacean detection and classification. Imagery was obtained at Lime Kiln Park, Washington from 7/6/10-7/9/10 using a FLIR Thermovision A40M Infrared camera (7.5-14μm, 37°HFOV, 320x240 pixels) under ideal atmospheric conditions (clear skies, calm seas, and wind speed 0-4 m/s). Whales were detected during both day (9 detections) and night (75 detections) at distances ranging from 42 to 162 m. The temperature contrast between dorsal fins and the sea surface ranged from 0.5 to 4.6 °C. Differences in emissivity from sea surface to dorsal fin are shown to aid detection at high incidence angles (near grazing). A comparison to theory is presented, and observed deviations from theory are investigated. A guide for Infrared camera selection based on site geometry and desired target size is presented, with specific considerations regarding marine mammal detection. Atmospheric conditions required to use visible and Infrared cameras for marine mammal detection are established and compared with 2008 meteorological data for the proposed tidal energy site. Using conservative assumptions, Infrared observations are predicted to provide a 74% increase in hours of possible detection, compared with visual observations.
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Relating Microwave Modulation to Microbreaking Observed in Infrared Imagery
IEEE Geoscience and Remote Sensing Letters, 2008Co-Authors: R. Branch, William J. Plant, Martin Gade, Andrew T JessupAbstract:Microwave modulation by swell waves and its relation to microbreaking waves were investigated in an ocean experiment. Simultaneous collocated microwave and Infrared (IR) measurements of wind waves and swell on the ocean were made. The normalized radar cross section sigma0 and the skin temperature T skin were both modulated by the swell, but with differing phases. In general, sigma0 maxima occurred on the front face, whereas T skin maxima occurred on the rear face of the swell. Infrared Imagery has shown that swell-induced microbreaking occurred at or near the swell crest and that the resulting warm wakes occurred on the rear face of the wave. When tilt and range modulations are taken into account, the location of microbreaking also accounts for the maximum of sigma0 occurring on the front face of the swell. Thus, microbreaking waves generated near the crest of low-amplitude swell can produce microwave and IR signatures with the observed phase. The relationship between microwave and IR signals was further emphasized by comparing microwave Doppler spectra with simultaneous IR and visible images of the sea surface from the same location. When small and microscale breaking waves were present, Doppler spectra exhibited characteristics that are similar to those from whitecaps, having peaks with large Doppler offsets and polarization ratios near unity. When no microbreakers were present, Doppler offsets and polarization ratios were much smaller in accordance with a composite surface scattering theory.
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Defining and quantifying microscale wave breaking with Infrared Imagery
Journal of Geophysical Research: Oceans, 1997Co-Authors: Andrew T Jessup, Christopher J. Zappa, Harry YehAbstract:Breaking without air entrainment of very short wind-forced waves, or microscale wave breaking, is undoubtedly widespread over the oceans and may prove to be a significant mechanism for enhancing the transfer of heat and gas across the air-sea interface. However, quantifying the effects of microscale wave breaking has been difficult because the phenomenon lacks the visible manifestation of whitecapping. In this brief report we present limited but promising laboratory measurements which show that microscale wave breaking associated with evolving wind waves disturbs the thermal boundary layer at the air-water interface, producing signatures that can be detected with Infrared Imagery. Simultaneous video and Infrared observations show that the Infrared signature itself may serve as a practical means of defining and characterizing the microscale breaking process. The Infrared Imagery is used to quantify microscale breaking waves in terms of the frequency of occurrence and the areal coverage, which is substantial under the moderate wind speed conditions investigated. The results imply that ”bursting“ phenomena observed beneath laboratory wind waves are likely produced by microscale breaking waves but that not all microscale breaking waves produce bursts. Oceanic measurements show the ability to quantify microscale wave breaking in the field. Our results demonstrate that Infrared techniques can provide the information necessary to quantify the breaking process for inclusion in models of air-sea heat and gas fluxes, as well as unprecedented details on the origin and evolution of microscale wave breaking.
Harry Yeh - One of the best experts on this subject based on the ideXlab platform.
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Defining and quantifying microscale wave breaking with Infrared Imagery
Journal of Geophysical Research: Oceans, 1997Co-Authors: Andrew T Jessup, Christopher J. Zappa, Harry YehAbstract:Breaking without air entrainment of very short wind-forced waves, or microscale wave breaking, is undoubtedly widespread over the oceans and may prove to be a significant mechanism for enhancing the transfer of heat and gas across the air-sea interface. However, quantifying the effects of microscale wave breaking has been difficult because the phenomenon lacks the visible manifestation of whitecapping. In this brief report we present limited but promising laboratory measurements which show that microscale wave breaking associated with evolving wind waves disturbs the thermal boundary layer at the air-water interface, producing signatures that can be detected with Infrared Imagery. Simultaneous video and Infrared observations show that the Infrared signature itself may serve as a practical means of defining and characterizing the microscale breaking process. The Infrared Imagery is used to quantify microscale breaking waves in terms of the frequency of occurrence and the areal coverage, which is substantial under the moderate wind speed conditions investigated. The results imply that ”bursting“ phenomena observed beneath laboratory wind waves are likely produced by microscale breaking waves but that not all microscale breaking waves produce bursts. Oceanic measurements show the ability to quantify microscale wave breaking in the field. Our results demonstrate that Infrared techniques can provide the information necessary to quantify the breaking process for inclusion in models of air-sea heat and gas fluxes, as well as unprecedented details on the origin and evolution of microscale wave breaking.