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Segmentation and Recognition Using Structure from Motion Point Clouds [chapter]

Gabriel J. Brostow, Jamie Shotton, Julien Fauqueur, Roberto Cipolla
2008 Lecture Notes in Computer Science  
The results confirm that indeed, accurate segmentation and recognition are possible using only motion and 3D world structure.  ...  We propose an algorithm for semantic segmentation based on 3D point clouds derived from ego-motion.  ...  Acknowledgements Thanks to John Winn for advice and for driving one of the capture cars.  ... 
doi:10.1007/978-3-540-88682-2_5 fatcat:27qraxd5j5frdc2htm62re56ji

A Real-Time and Multi-Sensor-Based Landing Area Recognition System for UAVs

Fei Liu, Jiayao Shan, Binyu Xiong, Zheng Fang
2022 Drones  
To solve this problem, firstly, we use a deep learning method to realize the landing area recognition and tracking from images.  ...  The problem is how to fuse the image and point cloud information and realize the landing area recognition to guide the UAV landing autonomously and safely.  ...  In this system, the motion change obtained by IMU is used to compensate for the motion of the LiDAR point clouds to obtain the point cloud data without motion distortion.  ... 
doi:10.3390/drones6050118 fatcat:c3bfbzvoxzcr5mze5powbmkcui

PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences [article]

Hehe Fan, Xin Yu, Yuhang Ding, Yi Yang, Mohan Kankanhalli
2022 arXiv   pre-print
Extensive experiments on widely-used 3D action recognition and 4D semantic segmentation datasets demonstrate the effectiveness of PSTNet to model point cloud sequences.  ...  Then, a spatial convolution is employed to capture the local structure of points in the 3D space, and a temporal convolution is used to model the dynamics of the spatial regions along the time dimension  ...  ACKNOWLEDGMENTS This research is supported by the Agency for Science, Technology and Research (A*STAR) under its AME Programmatic Funding Scheme (#A18A2b0046).  ... 
arXiv:2205.13713v1 fatcat:rgkx3kekcvaxtfiiytbh3sow7a

Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order Pooling [article]

Kavisha Vidanapathirana, Peyman Moghadam, Ben Harwood, Muming Zhao, Sridha Sridharan, Clinton Fookes
2021 arXiv   pre-print
This paper presents Locus, a novel place recognition method using 3D LiDAR point clouds in large-scale environments.  ...  Furthermore, Locus is demonstrated to be robust across several challenging situations such as occlusions and viewpoint changes in 3D LiDAR point clouds.  ...  Segments extracted from a LiDAR point cloud frame are described using two complementary sets of features.  ... 
arXiv:2011.14497v3 fatcat:zcxcao675bc6peaygucfcnk37y

3D object-based classification for vehicle extraction from airborne LiDAR data by combining point shape information with spatial edge

Wei Yao, Stefan Hinz, Uwe Stilla
2010 2010 IAPR Workshop on Pattern Recognition in Remote Sensing  
A 3D segmentation method working directly on point cloud is used, which features the detection of local arbitrary modes and the globally optimized organization of segments concurrently.  ...  The problem of vehicle extraction using airborne laser scanning (ALS) is studied under the framework of object-based point cloud analysis (OBPA).  ...  Vosselman from International Institute for Geo-Information Science and Earth Observation-ITC for providing the experimental dataset.  ... 
doi:10.1109/prrs.2010.5742804 fatcat:n37zf6l4nffy3fnn2v5rtgjtdm

Kinect-based Universal Range Sensor and its Application in Educational Laboratories

Mingshao Zhang, Zhou Zhang, Yizhe Chang, Sven K Esche, Constantin Chassapis
2015 International Journal of Online Engineering (iJOE)  
This approach consists of point cloud pre-processing with a focus on computational efficiency, object tracking employing recognition and post-processing including motion analysis.  ...  and used to animate the experimental device.  ...  Furthermore, the original data structure of the point clouds generated by the Kinect is kept and the recognition process can be implemented using a simple comparison.  ... 
doi:10.3991/ijoe.v11i2.4299 fatcat:wqhriaozy5c6nhreqq23ejb274

Recognition of Fingerspelling Sequences in Polish Sign Language Using Point Clouds Obtained from Depth Images

Dawid Warchoł, Tomasz Kapuściński, Marian Wysocki
2019 Sensors  
The paper presents a method for recognizing sequences of static letters of the Polish finger alphabet using the point cloud descriptors: viewpoint feature histogram, eigenvalues-based descriptors, ensemble  ...  Three kinds of the left-to-right Markov models of the transitions, two networks of the transition models—independent and dependent on a dictionary—as well as various combinations of point cloud descriptors  ...  Acknowledgments: The authors would like to express their deepest gratitude to the Deaf from the Subcarpathian Association of the Deaf for their kind assistance and support.  ... 
doi:10.3390/s19051078 fatcat:clmec7dcnjb6lipqwnyztg3eay

Fuji-SfM dataset: A collection of annotated images and point clouds for Fuji apple detection and location using structure-from-motion photogrammetry

Jordi Gené-Mola, Ricardo Sanz-Cortiella, Joan R. Rosell-Polo, Josep-Ramon Morros, Javier Ruiz-Hidalgo, Verónica Vilaplana, Eduard Gregorio
2020 Data in Brief  
The data provided in this article is related to the research article entitled "Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry" [1].  ...  Fuji) to reconstruct the 3D model of 11 trees by using structure-from-motion (SfM) photogrammetry.  ...  Fruit detection and 3D location using instance segmentation neural networks and structure-from-motion photogrammetry. (Submitted)  ... 
doi:10.1016/j.dib.2020.105591 pmid:32368602 pmcid:PMC7184157 fatcat:p37h74gpjvc2ngrmn2kwtg4r6q

Three-Dimensional Reconstruction of Structural Surface Model of Heritage Bridges Using UAV-Based Photogrammetric Point Clouds

Yue Pan, Yiqing Dong, Dalei Wang, Airong Chen, Zhen Ye
2019 Remote Sensing  
The point clouds of the heritage bridge are generated from the captured UAV images through the structure-from-motion workflow.  ...  Then, recognition by the use of a classification tree and bridge geometry is utilized to recognize different structural elements from the obtained segments.  ...  reconstruction, point cloud segmentation, and structural elements recognition.  ... 
doi:10.3390/rs11101204 fatcat:ibtxqwnsgzbxvfklxnfuhjmx3q

3D Point Cloud Descriptor for Posture Recognition

Margarita Khokhlova, Cyrille Migniot, Albert Dipanda
2018 Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications  
., Migniot, C. and Dipanda, A. 3D Point Cloud Descriptor for Posture Recognition.  ...  The proposed descriptor captures a point cloud structure by means of a modified 3D regular grid and a corresponding cells space occupancy information.  ...  In contrast to (Wang et al., 2016) , we do not use a descriptor for a given posture but aim to use a general 3D point cloud structure.  ... 
doi:10.5220/0006541801610168 dblp:conf/visapp/KhokhlovaMD18 fatcat:6oaxr2ehmvfkfhb6vzave6fp6q

Articulated Motion Segmentation of Point Clouds by Group-Valued Regularization [article]

Guy Rosman, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel
2012 Eurographics Workshop on 3D Object Retrieval, EG 3DOR  
In this paper we demonstrate an algorithm for articulated motion segmentation of 3D point clouds, free of any assumptions on the underlying model and yet firmly set in a well-defined variational framework  ...  Yet such a segmentation should be as free as possible from underlying assumptions so as to fit general scenes and objects.  ...  We demonstrate the segmentation of real point clouds obtained from laser scanners and Microsoft Kinect depth sensors.  ... 
doi:10.2312/3dor/3dor12/077-084 fatcat:zyrqu7df5rhsvfdpdgabsmgxwi

Smart Explorer: Recognizing Objects in Dense Clutter via Interactive Exploration [article]

Zhenyu Wu, Ziwei Wang, Zibu Wei, Yi Wei, Haibin Yan
2022 arXiv   pre-print
By aggregating the instance segmentation of RGB images across views, we acquire the instance-wise point cloud partition of the clutter through which the existed classes and the number of objects for each  ...  Specifically, we first collect the multi-view RGB-D images of the clutter and reconstruct the corresponding point cloud.  ...  The point cloud of the clutter is reconstructed from that collected from each view.  ... 
arXiv:2208.03496v1 fatcat:wcond7b7czdkrlszui6o7byb5u

Learning Visual Motion Segmentation Using Event Surfaces

Anton Mitrokhin, Zhiyuan Hua, Cornelia Fermuller, Yiannis Aloimonos
2020 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
The difficulty of the task stems from the fact that unlike in metric space, the shape of an object in (x, y, t) space depends on its motion and is not the same across the dataset.  ...  We evaluate our method on the state of the art event-based motion segmentation dataset -EV-IMO and perform comparisons to a frame-based method proposed by its authors.  ...  Since pixel motion is constrained by the laws of physics, the rigidity of bodies and the epipolar geometry, event clouds are significantly different from 3D point clouds in (x, y, z) space.  ... 
doi:10.1109/cvpr42600.2020.01442 dblp:conf/cvpr/MitrokhinHFA20 fatcat:ibmz64rxrnefpedu6hicgzckpu

Workbench for 3D target detection and recognition from airborne motion stereo and ladar imagery

Simon Roy, Stephen Se, Vinay Kotamraju, Jean Maheux, Christian Nadeau, Vincent Larochelle, Jonathan Fournier, Firooz A. Sadjadi, Abhijit Mahalanobis, Steven L. Chodos, William E. Thompson, David P. Casasent (+1 others)
2010 Automatic Target Recognition XX; Acquisition, Tracking, Pointing, and Laser Systems Technologies XXIV; and Optical Pattern Recognition XXI  
The database stores, manages, and edits input data of various types such as point clouds, video, still imagery frames, CAD models and metadata.  ...  The toolbox features data processing modules, including range data manipulation, surface mesh generation, texture mapping, and a shape-from-motion module to extract a 3D target representation from video  ...  ACKNOWLEDGMENTS The authors would like to thank the military personnel from the 12 e Régiment blindé du Canada, the 5 e Bataillon des services du Canada and the 430 e Escadron tactique d'hélicoptères,  ... 
doi:10.1117/12.849567 fatcat:cw7adnoxxbex7pldfpq27kdqsi


V. Barrile, G. Candela, A. Fotia
2019 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Point cloud analysis, and in particular segmentation and classification techniques, are actually used to identify objects within the scenes, assign to a specific class and use them for subsequent studies  ...  In this paper, starting from photogrammetric reconstruction, a methodology for segmentation and classification of point cloud based on image analysis is presented.  ...  for and matches for estimation of unknown camera parameters, 2) Application of Structure from Motion (SFM) algorithm and 3) Multi-View Stereo for 3d dense cloud generation.  ... 
doi:10.5194/isprs-archives-xlii-2-w11-187-2019 fatcat:2joipndb65du7fexuouidfgnii
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