Fast and Accurate Calibration of a Kinect Sensor

Raposo, Carolina; Barreto, João Pedro; Nunes, Urbano

doi:10.1109/3dv.2013.52

Cited by 53 publications

(51 citation statements)

References 10 publications

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“…In [8][9], the non-linear terms were adopted in the optimization which explicitly estimated the values of the parameters. It was noted [10] that such non-linearity could lead to low efficiency and cause unwanted instability in the numerical processing.…”

Section: Camera;mentioning

confidence: 99%

“…Many recent studies [8][9][10][13][14][15][16][17][18][19] proposed a depth measuring model and the corresponding calibration algorithms. Most of them are capable of calibrating depth and colour cameras at the same time.…”

Section: Related Workmentioning

confidence: 99%

“…In contrast, it is possible to use only a single checkerboard to jointly calibrate colour and depth camera [8][9][10] . [8] considers point correspondences between colour and depth images to identify intrinsic parameters.…”

Section: Related Workmentioning

confidence: 99%

“…However, with a high number of parameters to be optimized, they used a time-consuming iterative step to optimize parameters alternatively. Raposo et al [10] proposed several modifications of the optimization pipeline of [9] to improve the stability and the runtime. Follow-on studies [17][18][19] proposed the improved depth measuring models for depth camera.…”

Section: Related Workmentioning

confidence: 99%

“…Our implementation is based on previous studies which improved calibration accuracy by introducing the specific intrinsic parameters for both depth and colour cameras [8][9][10] and the novel depth measurement models [17][18][19] . In this paper, we propose a matrix of hybrid parameters as an alternation to the specific intrinsic parameters and propose a corresponding calibration algorithm, which solves the hybrid parameters with linear equations.…”

Section: Related Workmentioning

confidence: 99%

See 4 more Smart Citations

A Linear Approach for Depth and Colour Camera Calibration Using Hybrid Parameters

Cheng

Tong

et al. 2016

J. Comput. Sci. Technol.

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Many recent applications of computer graphics and human computer interaction have adopted both colour cameras and depth cameras as input devices. Therefore, an effective calibration of both types of hardware taking different colour and depth inputs is required. Our approach removes the numerical difficulties of using non-linear optimization in previous methods which explicitly resolve camera intrinsics as well as the transformation between depth and colour cameras. A matrix of hybrid parameters is introduced to linearize our optimization. The hybrid parameters offer a transformation from a depth parametric space (depth camera image) to a colour parametric space (colour camera image) by combining the intrinsic parameters of depth camera and a rotation transformation from depth camera to colour camera. Both the rotation transformation and intrinsic parameters can be explicitly calculated from our hybrid parameters with the help of a standard QR factorisation. We test our algorithm with both synthesized data and real-world data where ground-truth depth information is captured by Microsoft Kinect. The experiments show that our approach can provide comparable accuracy of calibration with the state-of-the-art algorithms while taking much less computation time (1/50 of Herrera's method and 1/10 of Raposo's method) due to the advantage of using hybrid parameters.

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Section: Camera;mentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

A Linear Approach for Depth and Colour Camera Calibration Using Hybrid Parameters

Cheng

Tong

et al. 2016

J. Comput. Sci. Technol.

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A system for the real‐time tracking of operant behavior as an application of 3D camera

Kuroda

2018

J Exper Analysis Behavior

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The capacity of 3D cameras to measure many different aspects of behavior (e.g., velocity, pattern, and posture) could contribute to the understanding of behavior. The present article describes a system for the real-time tracking of operant behavior, which is applicable to other domains of behavioral science as well. Methods for real-time 3D tracking of animal behavior are described, along with sample C++ programs. A demonstration using one zebrafish as a subject indicated that the present system successfully tracked the 3D motion of the fish. Moreover, the acquisition of a target response (i.e., approach to a corner of the aquarium) was demonstrated with the arrangement of a reinforcement contingency at the corner in the absence of a traditional, salient operandum. The system offers the capacity to characterize more completely ongoing behavior in learning tasks across a range of species than simply performance of discrete operant responses. The system also is capable of tracking multiple individuals simultaneously so it is possible both to study social interactions and arrange contingencies for engaging in social behavior. Other possible applications of 3D cameras are discussed.

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Calibration Between Depth and Color Sensors for Commodity Depth Cameras

Cha

Zhang

2014

Computer Vision and Machine Learning With RGB-D Sensors

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Fast and Accurate Calibration of a Kinect Sensor

Cited by 53 publications

References 10 publications

A Linear Approach for Depth and Colour Camera Calibration Using Hybrid Parameters

A Linear Approach for Depth and Colour Camera Calibration Using Hybrid Parameters

A system for the real‐time tracking of operant behavior as an application of 3D camera

Calibration Between Depth and Color Sensors for Commodity Depth Cameras

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