Extracted Feature Model from Point Cloud (Bosche 2012)
FKAConv: Feature-Kernel Alignment for Point Cloud Convolution
... 6.5 Filter visualization Our method FKAConv was derived from the discrete convolution on regular grids. The behavior of our 3D filters should thus be comparable to their 2D counterparts. In Figure 6, we present ...
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Feature-enhanced Surfaces from Incomplete Point Cloud with Segmentation and Curve Skeleton Information.
... Segmentation and 1D curve skeletons are adopted for surface extraction. Thus, building a complex shape can be divided into many simple subsets of building the parts with regular/simple shapes. Our approach requires fewer ...
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End-to-end learning of local point cloud feature descriptors
... kernel from the network trained on the ...The point activations highlight how this filter is not very robust to changes in orientation, since it is activated only when the surface is oriented in a ...
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Cloud Computing Tipping Point Model
... of cloud computing capability is gathering momentum ...outcomes from cloud computing is still greatly ...of cloud computing and investigates a model that an IT organisation can leverage ...
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FEATURE RELEVANCE ASSESSMENT FOR THE SEMANTIC INTERPRETATION OF 3D POINT CLOUD DATA
... 2.5 Feature Relevance Assessment and Feature Selection Once a variety of features has been extracted, it has to be consid- ered that these may contain redundant or irrelevant information with respect ...
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Point-cloud-based Model-mediated Teleoperation
... of model- mediated teleoperation (MMT) to six degrees-of-freedom in com- plex environments using a time-of-flight (ToF) ...a point cloud ...the point cloud model is captured by ...
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Facial feature point tracking based on a graphical model framework
... selected feature points and the spatial connections for head move- ment ...facial feature by ...facial feature, the algorithm continues tracking ...coming from data of the occluded ...
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A Novel Coarse to fine Registration for 3D Point Cloud Based on Feature Points
... geometry from a single aspect using 2D or 1D representations, and therefore suffer from limited descriptiveness and/or poor ...and point density to describe the point ...some feature ...
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Point Cloud Encoding for 3D Building Model Retrieval
... 3D point clouds, which is in a great need in the topic of efficient city model ...LiDAR point clouds and building models is the goal of this ...
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Graphical model based facial feature point tracking in a vehicle environment
... paper feature point tracking is performed in a frame- work that incorporates the temporal and spatial informa- tion between feature ...The model is based on a parametric model in which ...
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How To Create A Triangulation From A Point Cloud
... surface from point cloud ...the model, it can ignore outliers, patch holes and undersampled regions, and surmount ambiguity due to measurement ...
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The Application of Regional Combined Feature Variance Covariance Matrix in Point Cloud Similarity Measure
... matrix from eigenvectors for object detection and ...in point cloud ...contain point features other than region or topological features, it is common practice to screen out features that are ...
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Robust statistical approaches for feature extraction in laser scanning 3D point cloud data
... in point cloud data becomes complex because the points are usually unorganized, noisy, sparse, have inconsistent point density, have geometrical discontinuities, arbitrary surface shape with sharp ...
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Feature Sensitive Three-Dimensional Point Cloud Simplification using Support Vector Regression
... during point cloud data pre-processing is the reduction of number of ...be feature sensitive. Namely, dense point clouds are convenient for reconstruction of features that are represented by ...
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Shape-Matching Model Optimization Using Discrete-point Sampling and Feature Salience
... 1024) from the two sides and bottom of one freight car, where faults might ...cameras from each side take 7 photos each, and three cameras from the bottom side take 13 photos each, as ...taken ...
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Lidar point cloud and stereo image point cloud fusion
... math model approach was used to improve the registration of the OBC panoramic imagery to LiDAR ...achieved, from an RMS of 1.9m using the rigorous model to an RMS of ...registration point ...
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Fast and robust 3D feature extraction from sparse point clouds
... 3D point associated to the pixel D uv P , and p ⊥ uv be its 2D projection on the ...r from p ⊥ uv ...uv from the input point cloud P, and we set D P uv = 0 and I uv P = ...comes ...
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Dense Point Cloud Extraction From Oblique Imagery
... dense point clouds in an automated way. The extracted dense point cloud, instead of the LiDAR data, can be used to create the building ...dense point cloud gives higher ...
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From point cloud to BIM: a survey of existing approaches
... Approaches based on context Using this same heuristically logic, some modeling approaches based on context use relations between components. As a matter of example, (Xiong et al., 2010) uses this approach to model ...
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From Point Cloud to Grid DEM: A Scalable Approach
... Thinning point sets. Because LIDAR point sets can be very dense, there are often several cells in the output grid that contain multiple input points, especially when the grid cell size is ...far from ...
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