A computerized exchange network makes available on the Internet collected information of items under inspection, such as goods, real estate, or the like. In one aspect, the items and collected information, such as images and videos, are added to a virtual showroom or other virtual inspection site that presents an inventory of such goods, real estate, or the like available from multiple sellers and/or locations. In another aspect, detailed objective information about the items is provided. In another aspect, a data structure includes desired criteria for a desired item and provides an alert when an item of interest matches the desired criteria.

Compositing aware digital image search techniques and systems are described that leverage machine learning. In one example, a compositing aware image search system employs a two-stream convolutional neural network (CNN) to jointly learn feature embeddings from foreground digital images that capture a foreground object and background digital images that capture a background scene. In order to train models of the convolutional neural networks, triplets of training digital images are used. Each triplet may include a positive foreground digital image and a positive background digital image taken from the same digital image. The triplet also contains a negative foreground or background digital image that is dissimilar to the positive foreground or background digital image that is also included as part of the triplet.

The disclosed computer-implemented method may include (i) identifying, by a server computer system, a provider computing device for use in capturing street-level image data, where the provider computing device controls a camera positioned to capture street-level imagery outside the vehicle, (ii) determining, by the server computer system, a configuration that controls use of the provider computing device to provide street-level image data captured by the camera to the server computer system, (iii) sending, by the server computer system, the configuration to the computing device, and (iv) receiving, from the computing device, street-level image data captured by the computing device using the camera responsive to the configuration. Various other methods, systems, and computer-readable media are also disclosed.

A search refinement method and system to select items from a plurality of items using a user device connected via the internet to a server apparatus. The server apparatus includes a database of items and item attributes. Images of a first subset of the items are transmitted to the user device where they are presented on a display. A change indication selected by a user of the user device is received by the server apparatus, the change indication including at least one of an attribute selection and a reference item selected from the first subset. Responsive to receiving the change indication, an item score is computed for each of the items based on the item's attributes and the change indication. Images of a second subset of the items are presented on the user device. Each time the user initiates a change indication, another subset is presented on the user device, and the user can iteratively refine the search by finding items similar to the items represented by the change indication.

A content distribution apparatus generates a group of contents to be sent to a content display apparatus that can continuously display contents of the same attribute. When a first content is newly added to the group, the content distribution apparatus determines the attribute of the first content as the attribute of the group. When adding a second content to the group, if the attribute of the second content coincides with the attribute of the group, the content distribution apparatus adds the second content to the group. The content distribution apparatus sends a content included in the group to the content display apparatus.

In an example embodiment, a method is provided for image categorization. Here, images are displayed. In turn, a user input that describes a characteristic shared between the images from a comparison between the images is received. The user input may then be classified into categorization data.

An image search apparatus includes a display control device, a feature quantity calculation device, a scoring device for scoring the image based upon the values of the feature quantities calculated by the feature quantity calculation device, a first scoring control device, responsive to application of a first move command which moves an image being displayed in the candidate area to a search result area, for controlling the scoring device to raise the value of feature quantities, which correspond to the feature quantities of the image for which the first move command has been applied, and score the multiplicity of images based upon the raised values of the feature quantities, and an image placement decision device for deciding image placement in such a manner that a predetermined number of images having high scores obtained are displayed in the search result area, and other images are displayed in the candidate area.

An indication of a geographic area is received. Respective metrics of noteworthiness are obtained for multiple entities located in the geographic area. Using a machine-readable knowledge repository that describes semantic relations between the entities, several of the entities are selected in view of the corresponding metrics of noteworthiness, so that the selected entities share a set of attributes defining a commonality, and so that digital imagery is available for each of the selected entities. This commonality is not specified by the user. A geographic imagery tour that includes a representation of the respective digital imagery for the selected entities is generated.

Improved techniques for re-localizing Internet-of-Things (IOT) devices are disclosed herein. Sensor data digitally representing one or more condition(s) monitored by an IOT device is received. In response, a sensor readings map is accessed, where this map is associated with the IOT device. The map also digitally represents the IOT device's environment and includes data representative of a location of the IOT device within the environment. The map also includes data representative of the conditions monitored by the IOT device. Additionally, the map is updated by attaching the sensor data to the map. In some cases, a coverage map can also be computed. Both the sensors readings map and the coverage map can be automatically updated in response to the IOT device being re-localized.

A method for image labeling can include the following operations. An image to be labeled and a first scale indicator are acquired. A pixel neighborhood is constructed based on the first person point under the condition that the first scale indicator is more than or equal to a first threshold, the pixel neighborhood including a second pixel different from the first person point. A position of the second pixel is determined as the person point tag of the first person.