Measuring the distance of crowd movement objects to the camera using a stereo camera calibrated with object segmentation histogram of oriented gradient
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Published:
May 21, 2023
Keywords:
Calibrated Stereo Camera, Crowd Movement Object, Euclidian Distance camera, Histogram of Oriented Gradient, Measurement object
Section
Computer Science
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Abstract
Measuring the distance of objects to human objects is currently under development. In its development, a lot of research on measuring object distances was carried out in developing security systems and surveillance systems, one of which was in security in the environment of many human objects or crowds. This study uses the object segmentation method using the Histogram of Oriented Gradient feature to segment crowd objects. In determining the value of the distance based on information using a segmented object centroid. Calculations are performed using the Euclidian Distance calculation method to find the shortest distance between the centroid of the bounding box and the camera. The results of this study from object distance can distinguish human objects that have crowds with the best accuracy with a measurement error of 5.7%. The research have conclusion that the main findings produced can be used to produce an accurate human crowd object recognition system that is able to provide information on the value of the object's distance to the camera when the object.
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How to Cite
eka putera, B., Singgih Jatmiko and Ary Bima Kurniawan (2023) “Measuring the distance of crowd movement objects to the camera using a stereo camera calibrated with object segmentation histogram of oriented gradient”, Jurnal Mantik, 7(1), pp. 229-235. doi: 10.35335/mantik.v7i1.3711.
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Carrera, G.; Angeli, A.; Davison, A.J. SLAM-based automatic extrinsic calibration of a multi-camera rig. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Shanghai, China, 9–13 May 2011; pp. 2652–2659
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Ji, S.; Qin, Z.; Shan, J.; Lu, M. Panoramic SLAM from a multiple fisheye camera rig. ISPRS J. Photogramm. Remote Sens. 2020, 159, 169–183
Liu Y H, Jia Q X, Sun H X, Su J. Multi-camera calibration based on coplanar projection of points[C]// Computer Design and Applications (ICCDA), 2010 International Conference on. IEEE. 2010:V1-221– V1-224
Ricolfe-Viala C, Sanchez-Salmeron A J. Camera calibration under optimal conditions.[J]. Optics Express. 2011; 19(11):10769–75. doi: 10.1364/OE.19.010769 PMID: 21643333
Rohac, J.; Sipos, M.; Simanek, J. Calibration of low-cost triaxial inertial sensors. IEEE Instrum. Meas. Mag. 2015, 18, 32–38
Su, P.C.; Shen, J.; Xu, W.; Cheung, S.S.; Luo, Y. A Fast and Robust Extrinsic Calibration for RGB-D Camera Networks. Sensors 2018, 18, 235
Semeniuta, O. Analysis of camera calibration with respect to measurement accuracy. Procedia Cirp 2016, 41, 765–770.
Tsai R Y. A Versatile Camera Calibration Technique for High-Accuracy 3D Machine Vision Metrology Using Off-the-Shelf TV Cameras and Lenses[J]. IEEE Journal on Robotics and Automation. 1987; 3 (4):323–344
Tu, J.; Zhang, L. Effective data-driven calibration for a galvanometric laser scanning system using binocular stereo vision. Sensors 2018, 18, 197. [Google Scholar] [CrossRef] [PubMed][Green Version]
Ueshiba T, Tomita F. Plane-based Calibration Algorithm for Multi-camera Systems via Factorization of Homography Matrices[C]// IEEE International Conference on Computer Vision, 2003. Proceedings. IEEE. 2003:966–973
Wang, Y.; Liu, L.; Cai, B.; Wang, K.; Chen, X.; Wang, Y.; Tao, B. Stereo calibration with absolute phase target. Opt. Express 2019, 27, 22254–22267
Wang, H.; Mou, W.; Mou, X.; Yuan, S.; Ulun, S.; Yang, S.; Shin, B.-S. An automatic self-calibration approach for wide baseline stereo cameras using sea surface images. Unmanned Systs. 2015, 3, 277–290
Wang, Y.; Wang, X.; Wan, Z.; Zhang, J. A Method for Extrinsic Parameter Calibration of Rotating Binocular Stereo Vision Using a Single Feature Point. Sensors 2018, 18, 3666.
Wang, Y.; Rajamani, R. Direction cosine matrix estimation with an inertial measurement unit. Mech. Syst. Sig. Process. 2018
Yang J, Liu Y, Meng Q, Chu R. Objective Evaluation Criteria for Stereo Camera Shooting Quality Under Different Shooting Parameters and Shooting Distances[J]. IEEE Sensors Journal, 2015, 15 (8):1–1.
Yang J, Yang Q X, Qin P L. Two-dimensional flexible target for calibrating camera[J]. Optics & Precision Engineering. 2011; 19(5):1134–1142
Yang J, Yang Q X, Qin P L. Two-dimensional flexible target for calibrating camera[J]. Optics & Precision Engineering. 2011; 19(5):1134–1142
Zhang G. Unique world coordiantes based global calibration method for multi-vision inspection system [J]. Journal of Beijing University of Aeronautics & Astronautics. 2006; 32(11):1268–1272.
Zhang Z. A Flexible New Technique for Camera Calibration[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence. 2000; 22(11):1330–1334.
Zhou Z, Huang J, Wang J, Zhang K, Kuang Z. Object-Oriented Classification of Sugarcane Using Time-Series Middle-Resolution Remote Sensing Data Based on AdaBoost[J]. Plos One. 2015; 10 (11).
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