2365results about "Details involving processing steps" patented technology

The present invention provides a system (method and apparatus) for creating photorealistic 3D models of environments and/or objects from a plurality of stereo images obtained from a mobile stereo camera and optional monocular cameras. The cameras may be handheld, mounted on a mobile platform, manipulator or a positioning device. The system automatically detects and tracks features in image sequences and self-references the stereo camera in 6 degrees of freedom by matching the features to a database to track the camera motion, while building the database simultaneously. A motion estimate may be also provided from external sensors and fused with the motion computed from the images. Individual stereo pairs are processed to compute dense 3D data representing the scene and are transformed, using the estimated camera motion, into a common reference and fused together. The resulting 3D data is represented as point clouds, surfaces, or volumes. The present invention also provides a system (method and apparatus) for enhancing 3D models of environments or objects by registering information from additional sensors to improve model fidelity or to augment it with supplementary information by using a light pattern projector. The present invention also provides a system (method and apparatus) for generating photo-realistic 3D models of underground environments such as tunnels, mines, voids and caves, including automatic registration of the 3D models with pre-existing underground maps.

A capture system captures detectable attributes of a user. A differential system compares the detectable attributes with a normalized model of attributes, wherein the normalized model of attributes characterize normal representative attribute values across a sample of a plurality of users and generates differential attributes representing the differences between the detectable attributes and the normalized model of attributes. Multiple separate avatar creator systems receive the differential attributes and each apply the differential attributes to different base avatars to create custom avatars which reflect a selection of the detectable attributes of the user which are distinguishable from the normalized model of attributes.

A method and apparatus for performing two-dimensional video alignment onto three-dimensional point clouds. The system recovers camera pose from camera video, determines a depth map, converts the depth map to a Euclidean video point cloud, and registers two-dimensional video to the three-dimensional point clouds.

There is disclosed a depth information generation apparatus capable of acquiring high-precision depth information within a short computation time. A depth information generation apparatus of this invention generates depth information at the capture position of a reference image from the reference image, and at least one peripheral image that forms a stereo image pair with the reference image, and has a high-speed stereo processor (30) for generating depth information at high speed from the reference image and peripheral image, and a high-precision stereo processor (40) for generating high-precision depth information. A motion detector (20) detects a motion in an image, and instructs an image composition unit (50) to select the output from the high-speed stereo processor (30) for a portion with a large motion, and the output from the high-precision stereo processor (40) for other portions. The image composition unit (50) composites the outputs from the high-speed stereo processor (30) and high-precision stereo processor (40) in accordance with an instruction from the motion detector (20), and outputs a depth map as final depth information.

A method and apparatus for automatically combining aerial images and oblique images to form a three-dimensional (3D) site model. The apparatus or method is supplied with aerial and oblique imagery. The imagery is processed to identify building boundaries and outlines as well as to produce a depth map. The building boundaries and the depth map may be combined to form a 3D plan view model or used separately as a 2D plan view model. The imagery and plan view model is further processed to determine roof models for the buildings in the scene. The result is a 3D site model having buildings represented rectangular boxes with accurately defined roof shapes.

The present invention is embodied in a video flashlight method. This method creates virtual images of a scene using a dynamically updated three-dimensional model of the scene and at least one video sequence of images. An estimate of the camera pose is generated by comparing a present image to the three-dimensional model. Next, relevant features of the model are selected based on the estimated pose. The relevant features are then virtually projected onto the estimated pose and matched to features of the image. Matching errors are measured between the relevant features of the virtual projection and the features of the image. The estimated pose is then updated to reduce these matching errors. The model is also refined with updated information from the image. Meanwhile, a viewpoint for a virtual image is selected. The virtual image is then created by projecting the dynamically updated three-dimensional model onto the selected virtual viewpoint.

A system which resolves accuracy problems with 3D modeling techniques by using a 3D computer model that is updated using views provided by, say, a camera unit or camera system. The 2D images provided by matching the perspective view of an image within the model to that of an image of the environment. The 3D computer model can therefore be updated remotely, using 2D data.

Methods and systems for roof estimation are described. Example embodiments include a roof estimation system, which generates and provides roof estimate reports annotated with indications of the size, geometry, pitch and/or orientation of the roof sections of a building. Generating a roof estimate report may be based on one or more aerial images of a building. In some embodiments, generating a roof estimate report of a specified building roof may include generating a three-dimensional model of the roof, and generating a report that includes one or more views of the three-dimensional model, the views annotated with indications of the dimensions, area, and/or slope of sections of the roof. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

A 3D object modeling system and method system and method captures a 2D representation of the object to be modeled and breaks the 2D image into its geometric elements. The 3D stereoscopic image is then fitted to the geometric elements generated from the 2D image to generate the final model. The 3D stereoscopic image may be compared with the geometric elements to detect distortions in the object, allowing the distortions to be corrected in the final model to ensure that the model accurately depicts the original object.

A method of forming at least one three dimensional (3D) color image of at least one object in a target space. The method comprises projecting, each of a plurality of projection cycles, a sequence comprising a plurality of gray coded light patterns, each colored in one of red green or blue, on a target space, capturing a plurality of two dimensional (2D) images of the target space during a plurality of acquisition cycles, each the acquisition cycle being timed to correspond with the projection of at least a sub sequence of the sequence, the sub sequence comprising red, green, and blue gray coded light patterns of the plurality of gray coded light patterns, extracting range data and color texture information of at least one object in the target space from the plurality of 2D images, and forming a 3D color image of the range data and color texture information.

A method for processing an array of pixels in a point cloud, comprises calculating local error limits for each distance value for each pixel in the processed point cloud data set. One may then determine the error bar. One begins a distance value adjusting loop by for each pixel in the processed point cloud data set by calculating the difference between the distance value in the pixel of the point cloud data set being processed and each of the neighboring pixels or the most suitable neighboring pixel distance value is determined whether the difference is within the range defined by the error bar. It the difference is not within the error bar, the distance value is changed for the pixel being processed by a small fraction while keeping the new distance value within the range defined by the original distance value for the pixel being processed plus or minus the error bar. If the difference is within the error bar the distance value in the pixel being processed is replaced by a weighted average value. The number of neighboring pixels with their distance values within the error bar for the pixel being processed is counted and if the count is greater than a predetermined threshold, average the counted distance values and substitute the average for the pixel distance value, but if the count is below the threshold leave the pixel distance value unchanged. It is determined whether loop exit criteria have been met and if loop exit criteria have not been met beginning the loop again, and if loop exit criteria have been met, terminating the loop.

Apparatus and method for creating 3D imagery of an object using calibration means to transfer data to a reference frame and visibility analysis to determine and resolve occlusion.

An object's position and/or motion in three-dimensional space can be captured. For example, a silhouette of an object as seen from a vantage point can be used to define tangent lines to the object in various planes (“slices”). From the tangent lines, the cross section of the object is approximated using a simple closed curve (e.g., an ellipse). Alternatively, locations of points on an object's surface in a particular slice can also be determined directly, and the object's cross-section in the slice can be approximated by fitting a simple closed curve to the points. Positions and cross sections determined for different slices can be correlated to construct a 3D model of the object, including its position and shape. A succession of images can be analyzed to capture motion of the object.

The invention discloses a three-dimensional city modeling method based on BIM and GIS, comprising the following steps: data measurement, data processing, establishing BIM model, establishing three-dimensional GIS model, model fusion, municipal simulation, element separation and optimization, model rendering and display; through BIM, the precise height of the building can be easily obtained, appearance size and interior space information, thus through combining BIM and GIS, buildings are modeled first, and then the architectural spatial information is shared with the surrounding geographic environment, and applied to urban 3D GIS analysis, so that the cost of building spatial information can be reduced. At that same time, after the data is collected, point cloud and aerial photograph data are calculated and simulated by data classification comparison, so that the elevation information of the ground object is perfect, the elevation precision of the building model is high, and the roof ismore fine. The invention does not need a large amount of manual interaction modeling, and the data are collected by the unmanned aerial vehicle and the unmanned vehicle, and the efficiency is high, the production period is short, and the timeliness is strong.

A method of improving the lighting conditions of a real scene or video sequence. Digitally generated light is added to a scene for video conferencing over telecommunication networks. A virtual illumination equation takes into account light attenuation, lambertian and specular reflection. An image of an object is captured, a virtual light source illuminates the object within the image. In addition, the object can be the head of the user. The position of the head of the user is dynamically tracked so that an three-dimensional model is generated which is representative of the head of the user. Synthetic light is applied to a position on the model to form an illuminated model.

A method for estimating a camera motion and for determining a three-dimensional model of an environment is provided that includes the steps of: providing intrinsic parameters of a camera; providing a set of reference two-dimensional imaged points captured by the camera at a first camera pose and reference depth samples; determining a three-dimensional model of the environment; providing a set of current two-dimensional imaged points captured by the camera at a second camera pose and current depth samples associated to the set of current two-dimensional imaged points and determining a current three-dimensional model; estimating a camera motion between the first camera pose and the second camera pose; determining a similarity measure between the three-dimensional model and the current three-dimensional model, and if it is determined that the similarity measure meets a first condition, updating the three-dimensional model of the environment and adding the set of current two-dimensional imaged points to the set of reference two-dimensional imaged points.

The invention discloses an indoor scene 3D reconstruction method based on Kinect and solves the technical problem of the real-time reconstruction of an indoor scene 3D model and avoidance of excessive redundant points. The method comprises steps of: obtaining the depth data of an object by using Kinect and de-nosing and down-sampling the depth data; obtaining the point cloud data of a current frame and calculating the vector normal of each point in the frame; using a TSDF algorithm to establish a global data cube, and using a ray casting algorithm to calculate predicted point cloud data; calculating a point cloud registration matrix by using an ICP algorithm and the predicted point cloud data, fusing the obtained point cloud data of each frame into the global data cube, and fusing the point cloud data frame by frame until a good fusion effect is obtained; rendering the point cloud data with an isosurface extraction algorithm and constructing the 3D model of the object. The method improves the registration speed and the registration precision, is fast in fusion speed and few in redundancy points, and can be used for real-time reconstruction of the indoor scene.