A three-dimensional shape generation apparatus includes circuitry configured to generate three-dimensional shape information indicating a three-dimensional shape corresponding to a three-dimensional point group based on multiple sets of model shape information set by a model setting operation and point-group information indicating the three-dimensional point group. The model setting operation received at a reception screen sets the multiple sets of model shape information each indicating a three-dimensional model shape.

Disclosed is a rigging system for animating the detached and non-uniformly distributed data points of a point cloud. In response to a selection of a region of space in which a first set of data points are located, the system may identify commonality in the positional or non-positional elements of a first subset of the first set of data points, and may determine that a second subset of the first set of data points lack the commonality. The system may refine the first set of data points to a second set of data points that includes the first subset of data points and that excludes the second subset of data points. The system may link the second set of data points to a bone of a skeletal framework, and may animate the second set of data points based on an animation that is defined for the bone.

Techniques are disclosed for real-time mapping in a movable object environment. A system for real-time mapping in a movable object environment, may include at least one movable object including a computing device, a scanning sensor electronically coupled to the computing device, and a positioning sensor electronically coupled to the computing device. The system may further include a client device in communication with the at least one movable object, the client device including a visualization application which is configured to receive point cloud data from the scanning sensor and position data from the positioning sensor, record the point cloud data and the position data to a storage location, generate a real-time visualization of the point cloud data and the position data as it is received, and display the real-time visualization using a user interface provided by the visualization application.

A method, a system, and a computing device for reconstructing three-dimensional planes are provided. The method includes the following steps: obtaining a series of color information, depth information and pose information of a dynamic scene by a sensing device; extracting a plurality of feature points according to the color information and the depth information, and marking part of the feature points as non-planar objects including dynamic objects and fragmentary objects; computing point cloud according to the unmarked feature points and the pose information, and instantly converting the point cloud to a three-dimensional mesh; and growing the three-dimensional mesh to fill vacancy corresponding to the non-planar objects according to the information of the three-dimensional mesh surrounding or adjacent to the non-planar objects.

Aspects include a system and method for detection of computer-aided design (CAD) objects in point clouds. An example method includes obtaining, by a processing device, a labeled data set. The method further includes training, by the processing device, a model on the labeled data set using a two-dimensional (2D) object detector to calculate a three-dimensional (3D) box out of a detected 2D box by mapping coordinates on a geometric primitive image into 3D. The method further includes fitting, by the processing device, a computer-aided design (CAD) model into the 3D box.

A picking system is provided, which is capable of picking up an object even when the object is not registered in advance. The picking system includes: a picking device holding the object; an RGB-D camera acquiring three-dimensional point cloud data of the object to be picked up by the picking device; and a control device controlling the picking device based on a detection result by the RGB-D camera. The control device generates a geometric model of the object by combining simple geometric primitives while referring to the three-dimensional point cloud data, and calculates a holding position of the object for the picking device based on the geometric model.

The present invention relates to imaging a hollow organ. In order to provide an improved and facilitated imaging of a hollow organ of interest, a device (10) for providing three-dimensional data of a hollow organ is provided that comprises a measurement input (12), a data processor (14) and an output interface (16). The measurement input is configured to receive a plurality of local electric field measurements (18) of at least one electrode on a catheter inserted in a lumen of a hollow organ of interest. The measurement input is also configured to receive geometrical data (20) representative of the location of the at least one electrode inside the lumen during the measurements. The data processor is configured to receive pre-set electric field characteristics (22) associated with predetermined anatomical landmarks of the hollow organ expectable in the lumen in dependency of a type of the hollow organ. The data processor is also configured to compare at least one of the plurality of local electric field measurements with the pre-set electric field characteristics to determine matching electric field measurements. The data processor is further configured to allocate local electric field measurements to matching electric field characteristics based on the geometrical data to identify anatomical landmarks of the hollow organ by identifying those local field measurements in the plurality of measurements that correspond to landmarks of the hollow organ. The data processor is still further configured to generate a three-dimensional image data cloud (24) by transforming the allocated electric field measurements into portions of the three-dimensional image data cloud based on the identified anatomical landmarks. The output interface is configured to provide the three-dimensional image data cloud.

Methods and systems are disclosed that automatically determine solar access values. In one implementation, a 3D geo-referenced model of a structure is retrieved in which geographic location on the earth of points in the 3D geo-referenced model are stored or associated with points in the 3D geo-referenced model. Object point cloud data indicative of object(s) that cast shade on the structure is retrieved. The object point cloud data may be generated from one or more georeferenced images and the object point cloud data is indicative of an actual size, shape, and location of the object(s) on the earth. The structure in the 3D geo-referenced model is divided into one or more sections, which are divided into one or more areas, each area having at least three vertices. Then, a solar access value for the particular vertex is determined.

A device that executes a program stored in the memory to perform generating a local graph for the 3D point cloud based on distances and angles between 3D points in the 3D point cloud; matching the local graph using a similarity function and determining a feature matching pair in a matched local graph; and estimating a rigid body transformation matrix using the feature matching pair is provided.

Various implementations disclosed herein include devices, systems, and methods that generate floorplans and measurements using a three-dimensional (3D) representation of a physical environment generated based on sensor data.