International Journal of Multimedia Computing, 2022, 3(4); doi: 10.38007/IJMC.2022.030403.
Khadijaha Mansour
Jawaharlal Nehru University, India
With the progress of the times, more and more scientific and technological elements have been integrated into people’s daily life, which is manifested in fitting. Virtual fitting technology provides people with a more convenient and interactive fitting mode. The launch of Microsoft Kinect solves the problem of human body spatial information acquisition and facilitates the development of virtual fitting systems. This paper uses modeling software to build a human body 3D clothing model, and focuses on the human body 3D clothing modeling. This paper binds the three-dimensional clothing model with human bones to the user’s three-dimensional information collected through the Kinect camera to achieve the fusion of virtual and virtual clothing. This paper simulates the physical characteristics of clothing fabrics to improve the realism of virtual clothing degree. The iterative nearest point algorithm is improved. First, the voxel grid is down-sampled for the two point clouds, and then the scale-invariant feature points of the source point cloud are found and saved as a point cloud. The saved point cloud is registered with the target point cloud sampled from the voxel grid. In this paper, the human body point cloud data is collected through Kinect, and the point cloud segmentation, point cloud registration and point cloud reconstruction are studied separately, which makes the Kinect-based 3D human body modeling method more efficient and accurate. This paper proposes a method of iteratively deforming the standard model using the mesh deformation migration algorithm. The method is to establish a mapping relationship between models by given a set of corresponding point pairs between the source grid and the target grid, and realize the constrained deformation from the source grid to the target grid. Experiments show that the algorithm proposed in this paper uses a cheap depth camera to scan the human body. The algorithm preprocessing time is only about 1 second, and the average optimization time is about 3.6 seconds. It can overcome the shortcomings of low depth camera data accuracy, and the reconstruction time is short and the result is high accuracy.
Virtual Fitting, Kinect Technology, 3D Reconstruction, Augmented Reality
Khadijaha Mansour. 3D Reconstruction of Human Body in Virtual Fitting Room Based on Kinect. International Journal of Multimedia Computing (2022), Vol. 3, Issue 4: 29-40. https://doi.org/10.38007/IJMC.2022.030403.
[1] Figueroa N , Dong H , Saddik A E . A Combined Approach Toward Consistent Reconstructions of Indoor Spaces Based on 6D RGB-D Odometry and KinectFusion. ACM Transactions on Intelligent Systems and Technology, 2015, 6(2):1-10.https://doi.org/10.1145/2629673
[2] Boonbrahm P , Kaewrat C , Boonbrahm S . Realistic Simulation in Virtual Fitting Room Using Physical Properties of Fabrics. Procedia Computer Science, 2015, 7(5):12-16.https://doi.org/10.1016/j.procs.2015.12.189
[3] PMok K W , Wong C T , Choi S K , et al. Design and Development of Virtual Dressing Room System Based on Kinect. International Journal of Information Technology and Computer Science, 2018, 10(9):39-46.https://doi.org/10.5815/ijitcs.2018.09.05
[4] Wan Y , Lu J , Li A Q . Registration of 3D Point Cloud of Human Body Based on the Range Images and RGB Images. Applied Mechanics & Materials, 2015, 9(5):656-661.https://doi.org/10.4028/www.scientific.net/AMM.738-739.656
[5] J Sun, T Wang, Z D Li. Reconstruction of Vehicle-human Crash Accident and Injury Analysis Based on 3D Laser Scanning, Multi-rigid-body Reconstruction and Optimized Genetic Algorithm. Journal of Forensic Medicine, 2017, 33(6):575-582.
[6] Liu, Zhenbao, Huang, Jinxin, Bu, Shuhui. Template Deformation-Based 3-D Reconstruction of Full Human Body Scans From Low-Cost Depth Cameras. IEEE Transactions on Cybernetics, 2016:1-14.https://doi.org/10.1109/TCYB.2016.2524406
[7] Park H , Park J , Kim H , et al. Virtual Dress-Fitting Media Art System using Kinect and Augmented Reality. Techart Journal of Arts & Imaging ence, 2017, 4(2):10-12.https://doi.org/10.15323/techart.2017.05.4.2.10
[8] Liu Z , Huang J , Bu S , et al. Template Deformation-Based 3-D Reconstruction of Full Human Body Scans From Low-Cost Depth Cameras. IEEE TRANSACTIONS ON CYBERNETICS, 2017, 47(3):695-708.https://doi.org/10.1109/TCYB.2016.2524406
[9] Ebner T , Feldmann I , Renault S , et al. Multi‐view reconstruction of dynamic real‐world objects and their integration in augmented and virtual reality applications. Journal of the Society for Information Display, 2017, 25(3):151-157.https://doi.org/10.1002/jsid.538
[10] Chhaya M P , Melchels F P W , Holzapfel B M , et al. Sustained regeneration of high-volume adipose tissue for breast reconstruction using computer aided design and biomanufacturing. Biomaterials, 2015, 52(5):551-560.https://doi.org/10.1016/j.biomaterials.2015.01.025
[11] D.-Y. Lü, Huang Z P , Tao G H , et al. Dynamic Bayesian Network model based golf swing 3D reconstruction using simple depth imaging device. Journal of Electronics & Information Technology, 2015, 31(5):163-192.
[12] Yoon B , Choi K , Ra M , et al. Real-time Full-view 3D Human Reconstruction using Multiple RGB-D Cameras. Ie Transactions on Smart Processing & Computing, 2015, 4(4):224-230.https://doi.org/10.5573/IEIESPC.2015.4.4.224
[13] Hu P P , Li D , Wu G , et al. Personalized 3D mannequin reconstruction based on 3D scanning. International Journal of Clothing ence and Technology, 2018, 30(2):159-174.https://doi.org/10.1108/IJCST-05-2017-0067
[14] Takahashi K , Sakaguchi T , Ohya J . Remarks on a real-time, noncontact, nonwear, 3D human body posture estimation method. Systems & Computers in Japan, 2015, 31(14):1-10.https://doi.org/10.1002/1520-684X(200012)31:14<1::AID-SCJ1>3.0.CO;2-0
[15] Barbeito A , Painho M , Cabral P , et al. Beyond Digital Human Body Atlases: Segmenting an Integrated 3D Topological Model of the Human Body. International Journal of E-Health and Medical Communications (IJEHMC), 2017, 8(1):19-36.https://doi.org/10.4018/IJEHMC.2017010102
[16] Khan D , Shirazi M A , Kim M Y . Single shot laser speckle based 3D acquisition system for medical applications. Optics & Lasers in Engineering, 2018, 105(JUN.):43-53.https://doi.org/10.1016/j.optlaseng.2018.01.001
[17] Xu H , Li J , Lu G , et al. Modeling 3D Human Body with a Smart Vest. Computers & Graphics, 2018, 75(OCT.):44-58.https://doi.org/10.1016/j.cag.2018.07.005
[18] Liu Z , Sun H , Jin G , et al. Study of the Airflow Patterns and of the Characteristics of Bio-Aerosol Nanoparticle Deposition in Human Upper Respiratory Tracts Based on Computed Tomography Scanning Reconstruction. ence of Advanced Materials, 2016, 8(5):987-996.https://doi.org/10.1166/sam.2016.2654
[19] Zhu H , Liu Y , Fan J , et al. Video-Based Outdoor Human Reconstruction. IEEE Transactions on Circuits and Systems for Video Technology, 2017, 27(4):760-770.https://doi.org/10.1109/TCSVT.2016.2596118
[20] Xie L , Zhang X , Xu Y , et al. SkeletonFusion: Reconstruction and tracking of human body in real-time. Optics and Lasers in Engineering, 2018, 110(NOV.):80-88.https://doi.org/10.1016/j.optlaseng.2018.05.011
[21] Mao A , Zhang H W , Liu Y , et al. Easy and Fast Reconstruction of a 3D Avatar with an RGB-D Sensor. Sensors, 2017, 17(5):1113-1124.https://doi.org/10.3390/s17051113
[22] Vassilevski Y V , Danilov A A , Gamilov T M , et al. Patient-specific anatomical models in human physiology. Russian Journal of Numerical Analysis and Mathematical Modelling, 2015, 30(3):185-201.https://doi.org/10.1515/rnam-2015-0017
[23] Sekhavat Y A . Privacy Preserving Cloth Try-On Using Mobile Augmented Reality. IEEE Transactions on Multimedia, 2017, 19(5):1041-1049.https://doi.org/10.1109/TMM.2016.2639380
[24] Hendrawan Y F , Wahyuningrum R T , Siradjuddin I A , et al. Virtual Fitting Room Mobile Application for Madura Batik Clothes. Advanced ence Letters, 2016, 22(7):1783-1786.https://doi.org/10.1166/asl.2016.7043
[25] Wang M , Yu C , Fang F . Consumer awareness and function requirement of three-dimensional virtual fitting. Wool Textile Journal, 2017, 45(11):78-83.