A system allows a user to create new designs for apparel and preview these designs before manufacture. Software and lasers are used in finishing apparel to produce a desired wear pattern or other design. The user's preview may be based upon a two-dimensional image of a wear pattern in a laser input file and, from a set of two-dimensional images of a base garment, create a three-dimensional view of the base garment with the wear pattern.

An object identification and collection method is disclosed. The method includes receiving a pick-up path that identifies a route in which to guide an object-collection system over a target geographical area to pick up objects, determining a current location of the object-collection system relative to the pick-up path, and guiding the object-collection system along the pick-up path over the target geographical area based on the current location. The method further includes capturing images in a direction of movement of the object-collection system along the pick-up path, identifying a target object in the images; tracking movement of the target object through the images, determining that the target object is within range of an object picker assembly on the object-collection system based on the tracked movement of the target object, and instructing the object picker assembly to pick up the target object.

An object identification and collection method is disclosed. The method includes receiving a pick-up path that identifies a route in which to guide an object-collection system over a target geographical area to pick up objects, determining a current location of the object-collection system relative to the pick-up path, and guiding the object-collection system along the pick-up path over the target geographical area based on the current location. The method further includes capturing images in a direction of movement of the object-collection system along the pick-up path, identifying a target object in the images; tracking movement of the target object through the images, determining that the target object is within range of an object picker assembly on the object-collection system based on the tracked movement of the target object, and instructing the object picker assembly to pick up the target object.

The current document is directed to a dimensional shuffle transform (“DST”) that maps a 3D space to a one-dimensional space that preserves 3D neighborhoods within 1D neighborhoods within an implicit recursive hierarchical structure. The search for points in a 3D subspace is reduced, by the DST, to one or more searches in the transformed 1D space. The search is performed by either recursive decomposition of the 3D region indexed by the transform into subspaces, exploiting the transformed space structure, or by direct indexing into the region of interest. The searches over the subspaces generated by recursive decomposition are independent from one another, providing many opportunities for a variety of parallel, DST-enabled search methods.

Described herein are systems and methods of converting media dimensions. A device may identify a set of frames from a video in a first orientation as belonging to a scene. The device may receive a selected coordinate on a frame of the set of frames for the scene. The device may identify a first region within the frame including a first feature corresponding to the selected coordinate and a second region within the frame including a second feature. The device may generate a first score for the first feature and a second score for the second feature. The first score may be greater than the second score based on the first feature corresponding to the selected coordinate. The device may crop the frame to include the first region and the second region within a predetermined display area comprising a subset of regions of the frame in a second orientation.

Systems and methods for analyzing pathologies utilizing quantitative imaging are presented herein. Advantageously, the systems and methods of the present disclosure utilize a hierarchical analytics framework that identifies and quantify biological properties/analytes from imaging data and then identifies and characterizes one or more pathologies based on the quantified biological properties/analytes. This hierarchical approach of using imaging to examine underlying biology as an intermediary to assessing pathology provides many analytic and processing advantages over systems and methods that are configured to directly determine and characterize pathology from underlying imaging data.

Systems and methods for analyzing pathologies utilizing quantitative imaging are presented herein. Advantageously, the systems and methods of the present disclosure utilize a hierarchical analytics framework that identifies and quantify biological properties/analytes from imaging data and then identifies and characterizes one or more pathologies based on the quantified biological properties/analytes. This hierarchical approach of using imaging to examine underlying biology as an intermediary to assessing pathology provides many analytic and processing advantages over systems and methods that are configured to directly determine and characterize pathology from underlying imaging data.

Systems, methods, and non-transitory computer-readable media can obtain data associated with a computer-based experience. The computer-based experience can be based on interactive real-time technology. At least one virtual camera can be configured within the computer-based experience in a real-time engine. Data associated with an edit cut of the computer-based experience can be obtained based on content captured by the at least one virtual camera. A plurality of shots that correspond to two-dimensional content can be generated from the edit cut of the computer-based experience in the real-time engine. Data associated with a two-dimensional version of the computer-based experience can be generated with the real-time engine based on the plurality of shots. The two-dimensional version can be rendered based on the generated data.

An inference model construction method obtains a distribution of control points pertaining to a reference state and a distribution of the control points pertaining to a defined state with respect to a defined representation model. The method extracts a first feature value based on the distribution of the control points pertaining to the reference state. The method machine-learns the distribution of the control points pertaining to the defined state while using, as a label, the first feature value, and constructs an inference model based on a result of the leaning performed with respect to a plurality of the defined representation models.

An information processing device according to an embodiment includes a control unit that performs: control of switching a display coordinate system of display content from a first display coordinate system to a second display coordinate system, the display content displayed on a surface of a real object by a display unit, depending on a state of an input operation of changing a position or an angle of the display content; and control of changing a display position or a display angle of the display content in accordance with the second display coordinate system and causing the display unit to display input assist display corresponding to axes of the second display coordinate system in a case where the display coordinate system is switched from the first display coordinate system to the second display coordinate system.