Simple and robust tracking of hands and objects for video-based multimedia production

Itoh, M.; Ozeki, Makoto; Nakamura, Yutaka; Ohta, Yuichi

doi:10.1109/mfi-2003.2003.1232666

Cited by 8 publications

(8 citation statements)

References 2 publications

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“…As a result, subjects have difficulty feeling as they are actually touching a real object. We solve this problem by a skin color matting technique (Itoh et al, 2003) that utilizes a property that clusters the skin region in the chroma space. We defined a skin color model in chroma space in advance and segment the skin color region from captured images using the model.…”

Section: Elimination Of Occlusion By Image Mattingmentioning

confidence: 99%

Sensory Properties in Fusion of Visual/Haptic Stimuli Using Mixed Reality

Kitahara¹,

Nakahara²,

Ohta³

2010

Advances in Haptics

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Section: Elimination Of Occlusion By Image Mattingmentioning

confidence: 99%

Sensory Properties in Fusion of Visual/Haptic Stimuli Using Mixed Reality

Kitahara¹,

Nakahara²,

Ohta³

2010

Advances in Haptics

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“…The majority of the existing works in vision-based e-learning systems have focused on automatic camera control using single or multiple PTZ cameras to simulate human video shooting. The recent works are found in Onishi & Fukunaga (2004), Onishi et al (2000a), Bianchi (2004), Wallick et al 2004, Rui et al (2003), Itoh et al (2003), Ozeki et al (2002), Ozeki et al 2004, Kameda et al (2000), Kameda et al (2003) and Shimada et al (2004).…”

Section: Automatic Camera Controlmentioning

confidence: 97%

Rationale, Design and Implementation of a Computer Vision-Based Interactive E-Learning System

Jin

2007

International Journal of Distance Education Technologies

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This article presents a schematic application of computer vision technologies to e-learning that is synchronous, peer-to-peer-based, and supports an instructor's interaction with non-computer teaching equipments. The article first discusses the importance of these focused e-learning areas, where the properties include accurate bidirectional interaction and low cost hardware; system portability and versatile vision technology are emphasized. In the subsequent sections, we present some results aiming to achieve these goals. In particular, we highlight the most recent advancements in the interactive PTZ camera control from both the instructor and remote student. We also illustrated how these results have successfully addressed the challenges.

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“…It is impossible to accurately register objects at different observation depths under this assumption as the displacement and scaling for each object will depend on the varying perspective effects of the camera. This means that accurate registration can only occur when there is only one observed object in the scene [6] or when all the observed objects are restricted to lie at approximately the same distance from the camera [7]. The global alignment algorithms proposed by Irani & Anandan [8] and Coiras et al [9] do not account or experiment when there are objects at different depths or in different planes in the image.…”

Section: Related Researchmentioning

confidence: 99%

Registering Multimodal Imagery with Occluding Objects Using Mutual Information: Application to Stereo Tracking of Humans

Krotosky

Trivedi

Augmented Vision Perception in Infrared

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This chapter introduces and analyzes a method for registering multimodal images with occluding objects in the scene. An analysis of multimodal image registration gives insight into the limitations of assumptions made in current approaches and motivates the methodology of the developed algorithm. Using calibrated stereo imagery, we use maximization of mutual information in sliding correspondence windows that inform a disparity voting algorithm to demonstrate successful registration of objects in color and thermal imagery where there is significant occlusion. Extensive testing of scenes with multiple objects at different depths and levels of occlusion shows high rates of successful registration. Ground truth experiments demonstrate the utility of disparity voting techniques for multimodal registration by yielding qualitative and quantitative results that outperform approaches that do not consider occlusions. A framework for tracking with the registered multimodal features is also presented and experimentally validated. IntroductionComputer vision applications are increasingly using multimodal imagery to obtain and process information about a scene. Specifically, the disparate yet complementary nature of visual and thermal imagery has been used in recent works to obtain additional information and robustness [1,2]. The use of both types of imagery yields information about the scene that is rich in color, depth, motion, and thermal detail. Such information can then be used to successfully detect, track, and analyze people and objects in the scene.To associate the information from each modality, corresponding data in each image must be successfully registered. In long-range surveillance applications [2], the cameras are assumed to be oriented in such a way that a global alignment R.I. Hammoud (ed.), Augmented Vision Perception in Infrared: Algorithms and 321

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Simple and robust tracking of hands and objects for video-based multimedia production

Cited by 8 publications

References 2 publications

Sensory Properties in Fusion of Visual/Haptic Stimuli Using Mixed Reality

Sensory Properties in Fusion of Visual/Haptic Stimuli Using Mixed Reality

Rationale, Design and Implementation of a Computer Vision-Based Interactive E-Learning System

Registering Multimodal Imagery with Occluding Objects Using Mutual Information: Application to Stereo Tracking of Humans

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