@CONFERENCE{MTMT:2688560,
	title = {Sphere Fitting On MS Kinect Point Cloud},
	url = {https://m2.mtmt.hu/api/publication/2688560},
	author = {Molnár, Bence and Charles, K Toth and Dorota, A Grejner-Brzezinska},
	booktitle = {MAPPS/ASPRS 2012 Specialty Conference},
	unique-id = {2688560},
	abstract = {The Microsoft Kinect sensor is getting prominent in several 
		applications beyond the original field of videogames. The main 
		advantage of this 3D measurement device is the low price and 
		easy software development. Kinect has a Flash LiDAR type sensor 
		and RGB camera to provide colored 3D point cloud acquisition. 
		Based on previous accuracy investigations, the range calibration 
		results were found rather good for a low-end device. The 
		accuracy, however, can be further increased with more 
		sophisticated sensor calibration, especially by using the IR 
		intensity values for co-registration, as the number of matching 
		points between the depth and RGB images can be further 
		increased, which may yield to better calibration performance. 
		Previous experiences indicated some object distance dependent 
		scaling issues for depth calculation; objects farther than 2 
		meters are scaled down, caused by the measurement quantization 
		required for data transmission. In addition, the spacing of the 
		points is growing with the object distance. This means that the 
		common sphere fitting methods fail with Kinect on farther 
		objects. Therefore, a new fitting method was developed for 
		sphere fitting on Kinect acquired point cloud, which yields 
		better results, even over 2 meters. This way, the raw 
		measurement values can have high accuracy and, in particular, if 
		some preliminary information about the object morphology exists.},
	year = {2012},
	orcid-numbers = {Molnár, Bence/0000-0002-2602-2684}
}

@inproceedings{MTMT:2684494,
	title = {Calibrating the MS Kinect Sensor},
	url = {https://m2.mtmt.hu/api/publication/2684494},
	author = {Charles, K Toth and Molnár, Bence and Andrew, Zaydak and Dorota, A. Grejner-Brzezinska},
	booktitle = {ASPRS 2012 Annual Conference},
	unique-id = {2684494},
	abstract = {Flash LiDAR systems have been around for several years, but 
		their use was limited, mainly due to their poor performance. The 
		first generation products had range limitations and were quite 
		sensitive to ambient light conditions, basically restricting 
		their use to indoor applications. In addition, the high-noise 
		level provided for very low accuracy and stability. As 
		technology advanced, the Flash LiDAR sensors have shown gradual 
		improvements in performance, resulting in an increasing number 
		of applications. One of the most recently introduced inexpensive 
		sensors is the Microsoft Kinect, originally designed to support 
		gaming. Despite its low cost, the Kinect is very powerful, 
		providing a relatively dense point cloud and high-definition 
		video at high data rate. This paper reports about our 
		investigation with this sensor, including calibration 
		experiences and performance evaluation.},
	year = {2012},
	pages = {538-546},
	orcid-numbers = {Molnár, Bence/0000-0002-2602-2684}
}

@article{MTMT:2684910,
	title = {Accuracy Test of Microsoft Kinect for Human Morphologic Measurements},
	url = {https://m2.mtmt.hu/api/publication/2684910},
	author = {Molnár, Bence and Toth, C. K. and Detrekői, Ákos},
	doi = {10.5194/isprsarchives-XXXIX-B3-543-2012},
	journal-iso = {ISPRS (2002-)},
	journal = {INTERNATIONAL ARCHIVES OF PHOTOGRAMMETRY AND REMOTE SENSING (2002-)},
	volume = {39},
	unique-id = {2684910},
	issn = {1682-1750},
	abstract = {The Microsoft Kinect sensor, a popular gaming console, is widely 
		used in a large number of applications, including close-range 3D 
		measurements. This low-end device is rather inexpensive compared 
		to similar active imaging systems. The Kinect sensors include an 
		RGB camera, an IR projector, an IR camera and an audio unit. The 
		human morphologic measurements require high accuracy with fast 
		data acquisition rate. To achieve the highest accuracy, the 
		depth sensor and the RGB camera should be calibrated and co-
		registered to achieve high-quality 3D point cloud as well as 
		optical imagery. Since this is a low-end sensor, developed for 
		different purpose, the accuracy could be critical for 3D 
		measurement-based applications. Therefore, two types of accuracy 
		test are performed: (1) for describing the absolute accuracy, 
		the ranging accuracy of the device in the range of 0.4 to 15 m 
		should be estimated, and (2) the relative accuracy of points 
		depending on the range should be characterized. For the accuracy 
		investigation, a test field was created with two spheres, while 
		the relative accuracy is described by sphere fitting performance 
		and the distance estimation between the sphere center points. 
		Some other factors can be also considered, such as the angle of 
		incidence or the material used in these tests. The non-ambiguity 
		range of the sensor is from 0.3 to 4 m, but, based on our 
		experiences, it can be extended up to 20m. Obviously, this 
		methodology raises some accuracy issues which make accuracy 
		testing really important.},
	year = {2012},
	eissn = {2194-9034},
	pages = {543-547},
	orcid-numbers = {Molnár, Bence/0000-0002-2602-2684}
}