A number of embodiments can include a photographic chamber. In some embodiments, a photographic chamber can comprise one or more frames arranged in a convex shape and having an opening; one or more walls coupled to the one or more frames and having one or more recesses configured to receive photography equipment; and a door matching the one or more walls, wherein the door can be located in the opening when positioned in a closed configuration. Other embodiments are disclosed herein.

The present disclosure discloses an image processing method, apparatus, and a non-transitory computer readable medium. The method can includes: acquiring a three-dimensional (3D) model and original texture images of an object, wherein the original texture images are acquired by an imaging device; determining a mapping relationship between the 3D model and the original texture images of the object; determining, among the original texture images, a subset of texture images associated with a first perspective of the imaging device; splicing the subset of texture images into a spliced texture image corresponding to the first perspective; and mapping the spliced texture image to the 3D model according to the mapping relationship.

An image processing device acquires an image to be processed that includes an image of clothing, the image being composed of a hue, saturation and brightness; calculates a difference between the image to be processed and a plurality of shift images obtained by shifting the image to be processed in units of one pixel by at least one pixel or more in a prescribed direction, and generates a plurality of difference images that correspond to the number of shifted pixels; generates a histogram of differential pixel values for each of the hue, saturation and brightness of the difference images; determines the fabric of the clothing on the basis of the features of the histogram.

A machine may be configured to execute a machine-learning process for identifying and understanding fine properties of various items of various types by using images and associated corresponding annotations, such as titles, captions, tags, keywords, or other textual information applied to these images. By use of a machine-learning process, the machine may perform property identification accurately and without human intervention. These item properties may be used as annotations for other images that have similar features. Accordingly, the machine may answer user-submitted questions, such as What do rustic items look like?, and items or images depicting items that are deemed to be rustic can be readily identified, classified, ranked, or any suitable combination thereof.

A system, a method, and a computer program product for recognizing a logo from an image is provided. The method comprises receiving and preprocessing an image that contains the logo to be recognized. The method further comprises detecting text of the logo to recognize the logo. The method furthermore comprises extracting local and global features of a region of interest associated with the logo to recognize the logo if the text is not detected in the logo. The method further comprises detecting one or more signs in proximity of the logo to recognize the logo if the logo is not recognized by extracting the local and global features of the logo. The method finally comprises identifying a region where the logo is present in the pre-processed image to recognize the logo if the logo is not recognized by detecting the one or more signs in proximity of the logo.

A computer-implemented technique is described herein for performing an image-based search that allows a user to create a custom query image that expresses the user's search intent. The technique generates the query image based on one or more input images and/or one or more information items that describe at least one desired characteristic of the query image. The technique then submits the query image to a search engine, and, in response, receives a set of candidate images that match the query image. In one implementation, the technique constructs the query image using a decoder neural network that operates on a mixed latent variable vector. In one approach, the technique uses a generative adversarial network (GAN) to produce the decoder neural network.

The present disclosure discloses an image processing method, apparatus, and a non-transitory computer readable medium. The method can includes: acquiring a three-dimensional (3D) model and original texture images of an object, wherein the original texture images are acquired by an imaging device; determining a mapping relationship between the 3D model and the original texture images of the object; determining, among the original texture images, a subset of texture images associated with a first perspective of the imaging device; splicing the subset of texture images into a spliced texture image corresponding to the first perspective; and mapping the spliced texture image to the 3D model according to the mapping relationship.

There is provided a computer implemented method for predicting garment or accessory attributes using deep learning techniques, comprising the steps of: (i) receiving and storing one or more digital image datasets including images of garments or accessories; (ii) training a deep model for garment or accessory attribute identification, using the stored one or more digital image datasets, by configuring a deep neural network model to predict (a) multiple-class discrete attributes; (b) binary discrete attributes, and (c) continuous attributes, (iii) receiving one or more digital images of a garment or an accessory, and (iv) extracting attributes of the garment or the accessory from the one or more received digital images using the trained deep model for garment or accessory attribute identification. A related system is also provided.

The disclosure notably relates to a computer-implemented method for retrieving a similar virtual material appearance from a database. The method comprises providing a database including virtual material appearances associated to an appearance signatures computed from values representing at least one of a structure, a reflection and a color of the associated virtual material appearance. The method further comprises providing a first appearance signature associated to a first virtual material appearance. The method further comprises identifying one or to more virtual material appearances similar to the first virtual material appearance by comparing the first appearance signature with appearance signatures respectively associated to virtual material appearances in the database. The method improves retrieval of virtual material appearances.

A computer-based method of providing control commands of a control command set for manufacturing a three-dimensional object with an additive manufacturing device. The method includes at least the following steps: a step of allocating input data that represent at least a partial surface of the object to be manufactured, where the partial surface has an initial surface texture defined by a set of initial texture parameter values that characterize the geometry of the initial surface texture; a step of determining a set of target texture parameter values that differ from the set of initial texture parameter values, and a step of generating control commands of a control command set to manufacture the partial surface by the additive manufacturing device with a surface texture that is defined by the set of target texture parameter values.