The system and method deal with three-dimensional (3D) scanning technology which produces object representations which permit rapid, highly-accurate part identification which is not afforded by traditional two-dimensional (2D) camera imaging. The system and method are applicable to any field wherein repair/replacement parts are needed, such as the plumbing, automotive, fastener, marine, window, door, etc. fields

The present invention relates to a systems and methods to perform 3D localization of target objects in point cloud data using a corresponding 2D image. According to an illustrative embodiment of the present disclosure, a target environment is imaged with a camera to generate a 2D panorama and a scanner to generate a 3D point cloud. The 2D panorama is mapped to the point cloud with a 1 to 1 grid map. The target objects are detected and localized in 2D before being mapped back to the 3D point cloud.

The invention relates to computer implemented methods for generating a garment finish preset comprising assembly instructions for a garment finish for a garment to be fabricated, for automatically generating a garment finish preset comprising assembly instructions for a garment finish for a garment to be fabricated, and for automatically determining at least one candidate from a plurality of garment finish presets, each of said garment finish presets comprising assembly instructions for a garment finish for a garment to be fabricated from garment panels.

An obstacle detection method and device, an apparatus and a storage medium are provided, which are related to a field of intelligent transportation. The specific implementation includes: acquiring position information of a two-dimensional (2D) detection frame and position information of a three-dimensional (3D) detection frame of an obstacle in an image; converting the position information of the 3D detection frame of the obstacle into position information of a 2D projection frame of the obstacle; and optimizing the position information of the 3D detection frame of the obstacle by using the position information of the 2D detection frame, the position information of the 3D detection frame and the position information of the 2D projection frame of the obstacle in the image. Accuracy of results of predicting a 3D position of an obstacle by a roadside, on-board sensing device, or other sensing devices may be improved.

A lane departure warning system which uses at least one detection device, such as a stereo camera, to map the surrounding environment in three-dimensions, which provides for a determination of the distance of various objects in a given image obtained by the camera. With the information obtained by the camera, or cameras, additional data, such as the color of each pixel in an image, it is possible to identify which pixels in the image correspond to the road. Once the pixels that correspond to the road are identified, the width of the road is determined, as well as the position of the vehicle on the road. With the width of the road being known, the road is “virtually” divided into virtual lanes, and it is determined which of the virtual lanes the vehicle is travelling, and the vehicle is monitored to ensure that the vehicle remains within one of the virtual lanes.

A method is disclosed for creating a precision mask for a utility pole and/or pole hardware (“utility pole”) depicted in a digital image. The utility pole is detected within a digital image comprising a plurality of pixels. An initial pixel mask is then created for the utility pole and determining a color range. The plurality of pixels is then processed within the digital image, wherein: the color of each pixel is sampled, and each pixel is included or excluded from the precision mask based at least partially on its sampled color and the color range; and outputting the precision mask. Other disclosed methods provide for identification of a class of utility pole depicted in a digital image by comparison to a plurality of 3D models. Still other disclosed methods may be used to predict the height of a utility pole depicted in a digital image.

Apparatuses, components and methods are provided herein useful to provide assistance to customers and/or workers in a shopping facility. In some embodiments, a shopping facility personal assistance system comprises: a plurality of motorized transport units located in and configured to move through a shopping facility space; a plurality of user interface units, each corresponding to a respective motorized transport unit during use of the respective motorized transport unit; and a central computer system having a network interface such that the central computer system wirelessly communicates with one or both of the plurality of motorized transport units and the plurality of user interface units, wherein the central computer system is configured to control movement of the plurality of motorized transport units through the shopping facility space based at least on inputs from the plurality of user interface units.

A device may detect, in a field of view of a camera, one or more components of an automated teller machine (ATM) device using a computer vision technique based on generating a three dimensional model of the one or more components. The device may identify the ATM device as a particular device or as a particular type of device based on the one or more components of the ATM device, or first information related to the ATM device. The device may identify a set of tasks to be performed with respect to the ATM device. The device may provide, for display via a display associated with the device, second information associated with the set of tasks as an augmented reality overlay. The device may perform an action related to the set of tasks, the ATM device, or the augmented reality overlay.

An electronic device and method for texture map generation are disclosed. A set of color images from a set of viewpoints and depth information of a subject's face are acquired. A 3D model is generated based on a color image and the depth information. A set of viewpoint-specific projections of the 3D model are generated along the set of viewpoints. The 3D model is refined based on minimization of difference between each viewpoint-specific projection and a corresponding color image. A set of texture maps corresponding to the set of viewpoints is generated, based on the refined 3D model, and set of color images. A dynamic programming workflow is executed to determine seams along which respective portions of the set of texture maps are to be stitched and the respective portions are stitched along the seams to generate a final texture map for the refined 3D model of the subject's face.

Methods of determining the depth of a scene and associated systems are disclosed herein. In some embodiments, a method can include augmenting depth data of a scene captured with a depth sensor with depth data from one or more images of the scene. For example, the method can include capturing image data of the scene with a plurality of cameras. The method can further include generating a point cloud representative of the scene based on the depth data from the depth sensor and identifying a missing region of the point cloud, such as a region occluded from the view of the depth sensor. The method can then include generating depth data for the missing region based on the image data. Finally, the depth data for the missing region can be merged with the depth data from the depth sensor to generate a merged point cloud representative of the scene.