Abstract: During a training phase, a machine accesses reference images with corresponding depth information. The machine calculates visual descriptors and corresponding depth descriptors from this information. The machine then generates a mapping that correlates these visual descriptors with their corresponding depth descriptors. After the training phase, the machine may perform depth estimation based on a single query image devoid of depth information. The machine may calculate one or more visual descriptors from the single query image and obtain a corresponding depth descriptor for each visual descriptor from the generated mapping. Based on obtained depth descriptors, the machine creates depth information that corresponds to the submitted single query image.

Abstract: A configured machine performs image matching and retrieval of natural images that may depict logos. The machine generates and uses color-localized spatial masks, which may be computationally less expensive than spatial verification techniques. Key points are detected within images that form a reference database of images. Local masks are defined by the machine around each key point based on the scale and orientation of the key point. To utilize color information presented in logo images, ordered color histograms may be extracted by the machine from locally masked regions of each image. A cascaded index may then be constructed for both visual descriptors and color histograms. For faster matching, the cascaded index maps the visual descriptors and color histograms to a list of relevant or similar images. This list may then be ranked to generate relevant matches for an input query image.

Abstract: Apparatus and method for performing accurate text recognition of non-simplistic images (e.g., images with clutter backgrounds, lighting variations, font variations, non-standard perspectives, and the like) may employ a machine-learning approach to identify a discriminative feature set selected from among features computed for a plurality of irregularly positioned, sized, and/or shaped (e.g., randomly selected) image sub-regions.

Abstract: An apparatus and method for obtaining image feature data of an image are disclosed herein. A color histogram of the image is extracted from the image, the extraction of the color histogram including performing one-dimensional sampling of pixels comprising the image in each of a first dimension of a color space, a second dimension of the color space, and a third dimension of the color space. An edge map corresponding to the image is analyzed to detect a pattern included in the image. In response to a confidence level of the pattern detection being below a pre-defined threshold, extracting from the image an orientation histogram of the image. And identify a dominant color of the image.

Abstract: A machine may be configured to determine fashion preferences of users and to provide item recommendations to the users based on the users' fashion preferences. For example, the machine receives an image of a user and a set of spatial data indicating a position of the body of the user in a three-dimensional space. The machine may perform an analysis of the image and the set of spatial data. The performing of the analysis may include extracting, from the image, an image swatch that depicts a portion of an item worn by the user. The machine may identify a fashion preference of the user based on the analysis of the image and of the set of spatial data. The machine may identify an item that corresponds to the fashion preference of the user within an inventory of fashion items and may generate a recommendation of the identified fashion item.

Abstract: A machine may be configured to perform image evaluation of images depicting items for sale and to provide recommendations for improving the images depicting the items to increase the sales of the items depicted in the images. For example, the machine accesses a result of a user behavior analysis. The machine receives an image of an item from a user device. The machine performs an image evaluation of the received image based on an analysis of the received image and the result of the user behavior analysis. The performing of the image evaluation may include determining a likelihood of a user engaging in a desired user behavior in relation to the received image. Then, the machine generates, based on the evaluation of the received image, an output that references the received image and indicates the likelihood of a user engaging in the desired behavior.

Abstract: In various example embodiments, a system and method for image query are presented. A feature detector generates first feature description data of a first type. An image processor accesses feature codes and angle bins. The image processor generates second feature description data of a second type by comparing a plurality of groups with respective codes of the feature codes. Each of the plurality of groups comprises at least of portion of the first feature description data determined based at least on the feature codes and the angle bins. A search engine selects a first one of a plurality of stored feature description data linked to respective stored images. An interface provides an indication of the stored image linked to the first stored feature description data for display of the stored image linked to the first stored feature description data on a remote device.

Abstract: A method of processing an alloy workpiece to reduce thermal cracking may comprise spraying a metallic coating material onto at least a portion of a surface of the alloy workpiece to form a surface coating metallurgically bonded to the alloy workpiece. The surface coating may be more ductile than the alloy workpiece and reduces heat loss from the alloy workpiece.

Abstract: During a training phase, a machine accesses reference images with corresponding depth information. The machine calculates visual descriptors and corresponding depth descriptors from this information. The machine then generates a mapping that correlates these visual descriptors with their corresponding depth descriptors. After the training phase, the machine may perform depth estimation based on a single query image devoid of depth information. The machine may calculate one or more visual descriptors from the single query image and obtain a corresponding depth descriptor for each visual descriptor from the generated mapping. Based on obtained depth descriptors, the machine creates depth information that corresponds to the submitted single query image.

Abstract: Apparatus and method for performing accurate text recognition of non-simplistic images (e.g., images with clutter backgrounds, lighting variations, font variations, non-standard perspectives, and the like) may employ a machine-learning approach to identify a discriminative feature set selected from among features computed for a plurality of irregularly positioned, sized, and/or shaped (e.g., randomly selected) image sub-regions.

Abstract: 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.

Abstract: An apparatus and method to facilitate finding recommendations for a query image are disclosed herein. A color histogram is determined corresponding to the query image. Determining at least one of a visual pattern included in the query image, a dominant color of the query image, or an orientation histogram corresponding to the query image. Performing comparison of a first image attribute of the query image to a second image attribute of an inventory image corresponding to an inventory item, wherein the first image attribute used in the comparison is selected from among the color histogram, the dominant color, and the orientation histogram. The selection of the first image attribute is based on a confidence score associated with the visual pattern, the dominant color, or a directionality present in the query image.

Abstract: An apparatus and method to facilitate finding recommendations for a query image are disclosed herein. A color histogram is determined corresponding to the query image. Determining at least one of a visual pattern included in the query image, a dominant color of the query image, or an orientation histogram corresponding to the query image. Performing comparison of a first image attribute of the query image to a second image attribute of an inventory image corresponding to an inventory item, wherein the first image attribute used in the comparison is selected from among the color histogram, the dominant color, and the orientation histogram. The selection of the first image attribute is based on a confidence score associated with the visual pattern, the dominant color, or a directionality present in the query image.

Abstract: A system may be configured to calculate and use image sharpness results. In some example embodiments, a content-aware image sharpness evaluation scheme is implemented by the system to calculate the degree of sharpness or blur of photographs taken of objects of interest. In certain example embodiments, a calculated sharpness score from the image sharpness evaluation scheme is converted into a score that is meaningful relative to other photographs of the same category as the object depicted in the photograph. In various example embodiments, a mobile-based assistant is configured to provide instant (or near instant) feedback to users uploading photographs using a mobile device. In alternative example embodiments, a web-based assistant is configured to provide instant (or near instant) feedback to users uploading one or more photographs simultaneously to an electronic commerce or marketplace website.

Abstract: A surge protection circuit, a switching power supply, and a surge protection method are provided that can prevent a power supply from being damaged by a high energy surge voltage discharged from a terminal device to an output end of a power supply. The surge protection circuit is applied to the switching power supply. The power supply includes a transformer. The circuit includes a surge protection tube. When a surge voltage on the terminal device is greater than a discharge voltage of the surge protection tube, the surge protection tube is conducted and discharges the surge voltage on the terminal device to the ground wire end at the high voltage side of the transformer. The embodiments of the present invention are applicable to the field of electronic technologies.

Abstract: Providing fashion recommendations based on an image of clothing. Color, pattern, and/or style information corresponding to the clothing may be identified and used to find relevant clothing and/or accessories in an inventory to recommend to a user. The image may be a video of clothing and/or accessories on a human body in motion. An area thereof may be sampled, detected and tracked across sequential frames of the video to obtain color, pattern, and/or style information which may be compared against clothing and/or accessories in an inventory to provide real-time (or near real-time) recommendations to the user. The image may comprise clothing of interest that is associated with a celebrity. The celebrity may be specified and the system returns recommendations of items in the inventory that are matching or complementary to the clothing/accessory of interest and which are consistent with the particular celebrity's fashion style.

Abstract: In various example embodiments, a system and method for sketch based queries are presented. A sketch corresponding to a search item may be received from a user. At least a portion of the sketch may be generated by the user. An item attribute may be extracted from the sketch. The item attributed may correspond to a physical attribute of the search item. A set of inventory items similar to the search item may be identified based on the extracted item attribute and a search scope. The identified set of inventory items may be presented to the user.

Abstract: A method of processing an alloy workpiece to reduce thermal cracking may comprise spraying a metallic coating material onto at least a portion of a surface of the alloy workpiece to form a surface coating metallurgically bonded to the alloy workpiece. The surface coating may be more ductile than the alloy workpiece and reduces heat loss from the alloy workpiece.

Abstract: An apparatus and method for obtaining image feature data of an image are disclosed herein. A color histogram of the image is extracted from the image, the extraction of the color histogram including performing one-dimensional sampling of pixels comprising the image in each of a first dimension of a color space, a second dimension of the color space, and a third dimension of the color space. An edge map corresponding to the image is analyzed to detect a pattern included in the image. In response to a confidence level of the pattern detection being below a pre-defined threshold, extracting from the image an orientation histogram of the image. And identify a dominant color of the image.

Abstract: An apparatus and method for obtaining image feature data of an image are disclosed herein. A color histogram of the image is extracted from the image, the extraction of the color histogram including performing one-dimensional sampling of pixels comprising the image in each of a first dimension of a color space, a second dimension of the color space, and a third dimension of the color space. An edge map corresponding to the image is analyzed to detect a pattern included in the image. In response to a confidence level of the pattern detection being below a pre-defined threshold, extracting from the image an orientation histogram of the image. And identify a dominant color of the image.