Generating a texture image of a virtual fabric from a captured image involves generating similarity information about each similarity between a basic pattern included in a target analysis area and a plurality of sub areas which divide the target analysis area. At least one of information about a repetition number of the basic pattern and information about a repetition direction of the basic pattern is generated based on the similarity information. A texture image of a virtual fabric is generated by disposing a plurality of basic patterns in a predetermined area based on the basic pattern, the information about the repetition number and the information about the repetition direction.

System for generating textures on an object based on the particles emitted by a particle engine, including an access to data of a particles emitter, of particles emitted, of target object, of traces, and of graphical effects; an animation simulation module provided so as to perform a simulation of emission and of displacement for each of the particles provided; a tracer module provided for generating a trace on the surface of a target object corresponding to the displacement of a particle along said surface after an impact of the particle against the target object with the aid of the traces data and of the target object data; a physical parameters integrator module provided for generating a new set of textures for said object taking into account the data of the object, the data of each now or modified trace, and the data of the corresponding graphical effects. Corresponding method for generating textures.

System for generating textures on an object based on the particles emitted by a particle engine, including an access to data of a particles emitter, of particles emitted, of target object, of traces, and of graphical effects; an animation simulation module provided so as to perform a simulation of emission and of displacement for each of the particles provided; a tracer module provided for generating a trace on the surface of a target object corresponding to the displacement of a particle along said surface after an impact of the particle against the target object with the aid of the traces data and of the target object data; a physical parameters integrator module provided for generating a new set of textures for said object taking into account the data of the object, the data of each now or modified trace, and the data of the corresponding graphical effects. Corresponding method for generating textures.

In one embodiment, a method for detecting edge positions in a pattern structure is disclosed. The method includes detecting the edge positions of features within the pattern structure of an image without filtering the image, wherein the detecting is performed by: applying a model to a single linescan, adjusting, based on the single linescan, one or more parameters of the model, obtaining, using the one or more adjusted parameters, a best fit of the model to the single linescan.

In one embodiment, a method for detecting edge positions in a pattern structure is disclosed. The method includes detecting the edge positions of features within the pattern structure of an image without filtering the image, wherein the detecting is performed by: applying a model to a single linescan, adjusting, based on the single linescan, one or more parameters of the model, obtaining, using the one or more adjusted parameters, a best fit of the model to the single linescan.

In one embodiment, a method includes determining, by a processor, a measurement of edge detection noise; receiving a measurement of a biased parameter including measurement noise; based on the measurement of edge detection noise and a number of measurement points, determining a contribution of edge detection noise to the biased parameter; determining an unbiased parameter by subtracting the contribution of noise from the biased parameter including the measurement noise; and outputting the unbiased parameter.

In one embodiment, a method includes determining, by a processor, a measurement of edge detection noise; receiving a measurement of a biased parameter including measurement noise; based on the measurement of edge detection noise and a number of measurement points, determining a contribution of edge detection noise to the biased parameter; determining an unbiased parameter by subtracting the contribution of noise from the biased parameter including the measurement noise; and outputting the unbiased parameter.

Disclosed are systems and methods for rendering augmented videos on mobile devices and computing environment with limited computational resources. The disclosed systems and methods provide a novel framework for performing automatic detection of surfaces in video frames resulting in the creation of a seamless in-video augmentation object experience for viewing users. The disclosed framework operates by leveraging available surfaces in digital content to show augmentation objects in compliance with various pre-established contextual and technical constraints. The disclosed framework evidences a streamlined, automatic and computationally efficient process(es) that modifies digital content at the surface level within the frames of the digital content based on the contextual and technical constraints, and the computational resources of the device augmented digital content is rendered on.

Disclosed are systems and methods for rendering augmented videos on mobile devices and computing environment with limited computational resources. The disclosed systems and methods provide a novel framework for performing automatic detection of surfaces in video frames resulting in the creation of a seamless in-video augmentation object experience for viewing users. The disclosed framework operates by leveraging available surfaces in digital content to show augmentation objects in compliance with various pre-established contextual and technical constraints. The disclosed framework evidences a streamlined, automatic and computationally efficient process(es) that modifies digital content at the surface level within the frames of the digital content based on the contextual and technical constraints, and the computational resources of the device augmented digital content is rendered on.

A system and method for automating construction that includes collecting a multi-dimensional point cloud measurement of at least one construction structure that includes at least one surface; generating a construction plan from the multi-dimensional point cloud measurement, wherein the construction plan defines an assembly arrangement of a set of parts; from the construction plan, automatically generating a cut list for a subset of parts; communicating the cut list to a cutting device; and at the cutting device, cutting a set of materials according to the cut list.