Indoor Positioning and Navigation Using Time-Of-Flight Cameras

Kohoutek, Tobias K.; Droeschel, David; Mautz, Rainer; Behnke, Sven

doi:10.1007/978-3-642-27523-4_8

Cited by 8 publications

(4 citation statements)

References 8 publications

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“…There are only a few works that propose the use of range imaging systems to perform positioning tasks, probably because of the need for an initial calibration step and the high computational cost of image processing. In [ 30 , 31 ], the authors present an algorithm to identify the room where the camera is installed, via object detection and its comparison with a specific building database. No precise location inside the room is provided, though.…”

Section: Ultrasonic and Range Imaging Indoor Positioningmentioning

confidence: 99%

3D Indoor Positioning of UAVs with Spread Spectrum Ultrasound and Time-of-Flight Cameras

Paredes

Álvarez

Aguilera

et al. 2017

Sensors

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This work proposes the use of a hybrid acoustic and optical indoor positioning system for the accurate 3D positioning of Unmanned Aerial Vehicles (UAVs). The acoustic module of this system is based on a Time-Code Division Multiple Access (T-CDMA) scheme, where the sequential emission of five spread spectrum ultrasonic codes is performed to compute the horizontal vehicle position following a 2D multilateration procedure. The optical module is based on a Time-Of-Flight (TOF) camera that provides an initial estimation for the vehicle height. A recursive algorithm programmed on an external computer is then proposed to refine the estimated position. Experimental results show that the proposed system can increase the accuracy of a solely acoustic system by 70–80% in terms of positioning mean square error.

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Section: Ultrasonic and Range Imaging Indoor Positioningmentioning

confidence: 99%

3D Indoor Positioning of UAVs with Spread Spectrum Ultrasound and Time-of-Flight Cameras

Paredes

Álvarez

Aguilera

et al. 2017

Sensors

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“…Adding observations of an electronic compass and/or a tilt sensor would provide approximate values of some transformation parameters and therefore stabilize the search for the correct transformation set. Furthermore, if our approach will be used for an UVS equipped with a ToF camera additional problems like so-called mixed pixels or motion artifacts have to be solved by using filtering methods (e.g., [43,44]). Furthermore, the usage of spatial and semantic information of CityGML can be expended for pose estimation.…”

Section: Discussionmentioning

confidence: 99%

Fusion of Building Information and Range Imaging for Autonomous Location Estimation in Indoor Environments

Kohoutek

Mautz

Wegner

2013

Sensors

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We present a novel approach for autonomous location estimation and navigation in indoor environments using range images and prior scene knowledge from a GIS database (CityGML). What makes this task challenging is the arbitrary relative spatial relation between GIS and Time-of-Flight (ToF) range camera further complicated by a markerless configuration. We propose to estimate the camera's pose solely based on matching of GIS objects and their detected location in image sequences. We develop a coarse-to-fine matching strategy that is able to match point clouds without any initial parameters. Experiments with a state-of-the-art ToF point cloud show that our proposed method delivers an absolute camera position with decimeter accuracy, which is sufficient for many real-world applications (e.g., collision avoidance).

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“…In the process of logistics, TOF camera can obtain the volume of the packages quickly and track their locations, optimize the packing and shipping [8], [39]- [41].…”

Section: ) Logistics Industrymentioning

confidence: 99%

Recent Advances in 3D Data Acquisition and Processing by Time-of-Flight Camera

Chen

2019

IEEE Access

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Three-dimensional (3D) data acquisition and real-time processing is a critical issue in an artificial vision system. The developing time-of-flight (TOF) camera as a real-time vision sensor for obtaining depth images has now received wide attention, due to its great potential in many areas, such as 3D perception, computer vision, robot navigation, human-machine interaction, augmented reality, and so on. This paper survey advances in TOF imaging technology mainly from the last decade. We focus only on recent progress of overcoming limitations such as systematic errors, object boundary ambiguity, multipath error, phase wrapping, and motion blur, and address the theoretical principles and future research trends as well. INDEX TERMS Vision sensor, time of flight, depth image, sensing device, computer vision, 3D vision.

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Indoor Positioning and Navigation Using Time-Of-Flight Cameras

Cited by 8 publications

References 8 publications

3D Indoor Positioning of UAVs with Spread Spectrum Ultrasound and Time-of-Flight Cameras

3D Indoor Positioning of UAVs with Spread Spectrum Ultrasound and Time-of-Flight Cameras

Fusion of Building Information and Range Imaging for Autonomous Location Estimation in Indoor Environments

Recent Advances in 3D Data Acquisition and Processing by Time-of-Flight Camera

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