A large synthetic 3D human body model dataset using real-world body size distributions is created. The model dataset may follow real-world body parameter distributions. Depth sensors can be integrated into mobile devices such as tablets, cellphones, and wearable devices. Body measurements for a user are extracted from a single frontal-view depth map using joint location information. Estimates of body measurements are combined with local geometry features around joint locations to form a robust multi-dimensional feature vector. A fast nearest-neighbor search is performed using the feature vector for the user and the feature vectors for the synthetic models to identify the closest match. The retrieved model can be used in various applications such as clothes shopping, virtual reality, online gaming, and others.
In various example embodiments, a system and method for integration of a three-dimensional model is disclosed. In one example embodiment, a method includes receiving a plurality of images, selecting points on the images and triangulating the points to generate a plurality of depth maps, generate a three-dimensional mesh by combining the plurality of depth maps, generating a three-dimensional model of the item by projecting the plurality of images onto the mesh using the points, calibrating colors used in the model using colors diffuse properties of the colors in the images, and providing a user interface allowing a user to select one or more user points on the three-dimensional model and provide additional information associated with the selected user points.
Techniques for automatically modulating a physical configuration of a reconfigurable building structure. A reconfigurable building structure may be constructed of physical elements that are movable with respect to one another to facilitate actuating the reconfigurable building structure between a plurality of different physical configurations. The physical configuration of a reconfigurable building structure may be adjusted to accommodate for physical dimensions of an item that is going to be moved into the reconfigurable building structure. For example, a spacing between two shelves may be expanded in response to an order being placed for a large item. In this way, when the item is delivered to a physical address associated with the reconfigurable building structure, various physical characteristics of the reconfigurable building structure may have already been modulated to accept the item.
Camera platform techniques are described. In an implementation, a plurality of digital images and data describing times, at which, the plurality of digital images are captured is received by a computing device. Objects of clothing are recognized from the digital images by the computing device using object recognition as part of machine learning. A user schedule is also received by the computing device that describes user appointments and times, at which, the appointments are scheduled. A user profile is generated by the computing device by training a model using machine learning based on the recognized objects of clothing, times at which corresponding digital images are captured, and the user schedule. From the user profile, a recommendation is generated by processing a subsequent user schedule using the model as part of machine learning by the computing device.
In various example embodiments, a system and method for determining an item that has confirmed characteristics are described herein. An image that depicts an object is received from a client device. Structured data that corresponds to characteristics of one or more items are retrieved. A set of characteristics is determined, the set of characteristics being predicted to match with the object. An interface that includes a request for confirmation of the set of characteristics is generated. The interface is displayed on the client device. Confirmation that at least one characteristic from the set of characteristics matches with the object depicted in the image is received from the client device.
The disclosed technologies include a robotic selling assistant that receives an item from a seller, automatically generates a posting describing the item for sale, stores the item until it is sold, and delivers or sends the item out for delivery. The item is placed in a compartment that uses one or more sensors to identify the item, retrieve supplemental information about the item, and take pictures of the item for inclusion in the posting. A seller-supplied description of the item may be verified based on the retrieved supplemental information, preventing mislabeled items from being sold.
Systems, methods, and computer program products for identifying a relevant candidate product in an electronic marketplace. Embodiments perform a visual similarity comparison between candidate product image visual content and input query image visual content, process formal and informal natural language user inputs, and coordinate aggregated past user interactions with the marketplace stored in a knowledge graph. Visually similar items and their corresponding product categories, aspects, and aspect values can determine suggested candidate products without discernible delay during a multi-turn user dialog. The user can then refine the search for the most relevant items available for purchase by providing responses to machine-generated prompts that are based on the initial search results from visual, voice, and/or text inputs. An intelligent online personal assistant can thus guide a user to the most relevant candidate product more efficiently than existing search tools.
Methods, systems, and computer programs are presented for adding new features to a network service. A method includes receiving an image depicting an object of interest. A category set is determined for the object of interest and an image signature is generated for the image. Using the category set and the image signature, the method identifies a set of publications within a publication database and assigns a rank to each publication. The method causes presentation of the ranked list of publications at a computing device from which the image was received.
Methods, systems, and computer programs are presented for adding new features to a network service. A method includes receiving an image depicting an object of interest. A category set is determined for the object of interest and an image signature is generated for the image. Using the category set and the image signature, the method identifies a set of publications within a publication database and assigns a rank to each publication.The method causes presentation of the ranked list of publications at a computing device from which the image was received.
Camera platform and object inventory control techniques are described. In an implementation a live feed of digital images is output in a user interface by a computing device. A user selection is received through interaction with the user interface of at least one of the digital images. An object, included within the at least one digital image, is recognized using machine learning. Metadata is then obtained that pertains to the recognized object. Augmented reality digital content is generated based at least in part of the obtained metadata. The augmented reality digital content is displayed as part of the live feed of digital images as associated with the object.
In various example embodiments, a system and method for determining an item that has confirmed characteristics are described herein. An image that depicts an object is received from a client device. Structured data that corresponds to characteristics of one or more items are retrieved. A set of characteristics is determined, the set of characteristics being predicted to match with the object. An interface that includes a request for confirmation of the set of characteristics is generated. The interface is displayed on the client device. Confirmation that at least one characteristic from the set of characteristics matches with the object depicted in the image is received from the client device.
Methods, systems, and computer programs are presented for adding new features to a network service. A method includes receiving an image depicting an object of interest. A category set is determined for the object of interest and an image signature is generated for the image. Using the category set and the image signature, the method identifies a set of publications within a publication database and assigns a rank to each publication. The method causes presentation of the ranked list of publications at a computing device from which the image was received.
In various example embodiments, a system and method for determining an item that has confirmed characteristics are described herein. An image that depicts an object is received from a client device. Structured data that corresponds to characteristics of one or more items are retrieved. A set of characteristics is determined, the set of characteristics being predicted to match with the object. An interface that includes a request for confirmation of the set of characteristics is generated. The interface is displayed on the client device. Confirmation that at least one characteristic from the set of characteristics matches with the object depicted in the image is received from the client device.
In various example embodiments, a system and method for integration of a three-dimensional model is disclosed. In one example embodiment, a method includes receiving a plurality of images, selecting points on the images and triangulating the points to generate a plurality of depth maps, generate a threedimensional mesh by combining the plurality of depth maps, generating a threedimensional model of the item by projecting the plurality of images onto the mesh using the points, calibrating colors used in the model using colors diffuse properties of the colors in the images, and providing a user interface allowing a user to select one or more user points on the three-dimensional model and provide additional information associated with the selected user points.
Methods, systems, and computer programs are presented for adding new features to a network service. An example method includes accessing an image from a user device to determine a salient object count of a plurality of objects in the image. A salient object count of the plurality of objects in the image is determined. An indicator of the salient object count of the plurality of objects in the image is caused to be displayed on the user device.
Camera platform techniques are described. In an implementation, a plurality of digital images and data describing times, at which, the plurality of digital images are captured is received by a computing device. Objects of clothing are recognized from the digital images by the computing device using object recognition as part of machine learning. A user schedule is also received by the computing device that describes user appointments and times, at which, the appointments are scheduled. A user profile is generated by the computing device by training a model using machine learning based on the recognized objects of clothing, times at which corresponding digital images are captured, and the user schedule. From the user profile, a recommendation is generated by processing a subsequent user schedule using the model as part of machine learning by the computing device.
In various example embodiments, a system and method are provided for automated estimation of a saliency map for an image based on a graph structure comprising nodes corresponding to respective superpixels on the image, the graph structure including boundary-connecting nodes that connects each non-boundary node to one or more boundary regions. Each non-boundary node is in some embodiments connected to all boundary nodes by respective boundary-connecting edges forming part of the graph. Edge weights are calculated to generate a weighted graph. Saliency map estimation comprises bringing respective nodes for similarity to a background query. The edge weights of at least some of the edges are in some embodiments calculated as a function of a geodesic distance or shortest path between the corresponding nodes.
In various example embodiments, a system and method for determining an item that has confirmed characteristics are described herein. An image that depicts an object is received from a client device. Structured data that corresponds to characteristics of one or more items are retrieved. A set of characteristics is determined, the set of characteristics being predicted to match with the object. An interface that includes a request for confirmation of the set of characteristics is generated. The interface is displayed on the client device. Confirmation that at least one characteristic from the set of characteristics matches with the object depicted in the image is received from the client device.
A large synthetic 3D human body model dataset using real-world body size distributions is created. The model dataset may follow real-world body parameter distributions. Depth sensors can be integrated into mobile devices such as tablets, cellphones, and wearable devices. Body measurements for a user are extracted from a single frontal-view depth map using joint location information. Estimates of body measurements are combined with local geometry features around joint locations to form a robust multi-dimensional feature vector. A fast nearest-neighbor search is performed using the feature vector for the user and the feature vectors for the synthetic models to identify the closest match. The retrieved model can be used in various applications such as clothes shopping, virtual reality, online gaming, and others.
