Cluster tracking with Time-of-Flight cameras

Hansen, Dan Witzner; Hansen, Michael Sass; Kirschmeyer, Martin; Larsen, Rasmus; Silvestre, D.

doi:10.1109/cvprw.2008.4563156

Cited by 18 publications

(3 citation statements)

References 7 publications

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“…A refined shape‐from‐silhouette technique, based on an initial binary foreground segmentation for RGB‐ and range data, is used to construct the visual hulls for the people to be tracked. Another different tracking approach has been discussed in [HHK*08]. Here, only one ToF camera is used to observe a scene at an oblique angle.…”

Section: User Interaction and User Trackingmentioning

confidence: 99%

Time‐of‐Flight Cameras in Computer Graphics

Kolb

Barth

Koch

et al. 2010

Computer Graphics Forum

318

228

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A growing number of applications depend on accurate and fast 3D scene analysis. Examples are model and lightfield acquisition, collision prevention, mixed reality and gesture recognition. The estimation of a range map by image analysis or laser scan techniques is still a time-consuming and expensive part of such systems. A lower-priced, fast and robust alternative for distance measurements are time-of-flight (ToF) cameras. Recently, significant advances have been made in producing low-cost and compact ToF devices, which have the potential to revolutionize many fields of research, including computer graphics, computer vision and human machine interaction (HMI).These technologies are starting to have an impact on research and commercial applications. The upcoming generation of ToF sensors, however, will be even more powerful and will have the potential to become 'ubiquitous real-time geometry devices' for gaming, web-conferencing, and numerous other applications. This paper gives an account of recent developments in ToF technology and discusses the current state of the integration of this technology into various graphics-related applications.

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Section: User Interaction and User Trackingmentioning

confidence: 99%

Time‐of‐Flight Cameras in Computer Graphics

Kolb

Barth

Koch

et al. 2010

Computer Graphics Forum

318

228

View full text Add to dashboard Cite

show abstract

“…The estimation of 3D pose and camera motion using a TOF camera is proposed in [3], [4]. Moreover, the effectiveness of the TOF camera has been shown in [5], [6], JAREE-Journal on Advanced Research in Electrical Engineering Volume 2, Number 1, April 2018 by applying the sensor to the tracking of the head and objects and the detection of people. However those studies focused only on three-dimensional information obtained by the TOF camera.…”

Section: Ccd Cameras Tof Cameramentioning

confidence: 99%

A Visual Sensor for Domestic Service Robots

Attamimi

Nagai

2018

JAREE

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In this study, we present a visual sensor for domestic service robots, which can capture both color information and three-dimensional information in real time, by calibrating a time of flight camera and two CCD cameras. The problem of occlusions is solved by the proposed occlusion detection algorithm. Since the proposed sensor uses two CCD cameras, missing color information of occluded pixels is compensated by one another. We conduct several evaluations to validate the proposed sensor, including investigation on object recognition task under occluded scenes using the visual sensor. The results revealed the effectiveness of proposed visual sensor.

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“…A lot of approaches have been used for obtaining a good ToF-based tracking. In [6] the retrieved clusters are projected on the ground plane for creating a so called "flat-map", then an Expectation Maximization algorithm has been applied to that map. A method for multiple people tracking based on Shape from Silhouettes (SfS) is proposed in [7]: it appears robust but greatly limited by the high numbers of the cams needed (six in the proposed solution) and by the small dimension of the room.…”

Section: State Of Artmentioning

confidence: 99%

Multisubjects Tracking by Time-of-Flight Camera

Dondi

Lombardi

Cinque

2013

Image Analysis and Processing – ICIAP 2013

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Time-of-Flight cameras are the state of art sensors for a fast detection of depth data in a scene. This kind of sensors can be very useful for tracking, in particular in indoor ambient, since, using light in near-infrared spectrum, they are less affected by abrupt change in illumination. In this paper we propose a new method for the tracking of multiple subjects based on Kalman filter. The first step of our solution is a ToF based foreground segmentation, that retrieves all significant clusters in the scene, followed by a robust tracking system able to correctly handle occlusions and possible merging between clusters.

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Cluster tracking with Time-of-Flight cameras

Abstract: We describe a method for tracking people using a

Cited by 18 publications

References 7 publications

Time‐of‐Flight Cameras in Computer Graphics

Time‐of‐Flight Cameras in Computer Graphics

A Visual Sensor for Domestic Service Robots

Multisubjects Tracking by Time-of-Flight Camera

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