Abstract: Embodiments disclosed herein provide for a system and method for recalibrating an augmented reality experience in mobile devices using a plurality of physical markers. The system and methods provide for realigning the digital representation to the physical world using known physical locations associated with the physical markers that map directly to the digital representation.

Abstract: A device having extended reality capabilities receives a video feed including one or more video frames depicting an object. The device provides the one or more video frames to a first machine learning model that identifies the object and one or more parts of the object that are depicted in the one or more video frames, and obtains positional tracking information that represents a position and an orientation associated with the object depicted in the one or more video frames relative to a coordinate space. The device identifies a plurality of parts from the one or more parts of the object that are depicted in the one or more video frames and determines, using one or more second machine learning models, information regarding the plurality of parts and information regarding one or more replacement parts.

Abstract: A device receives image data of a contractual document that includes an offer including terms of a proposed transaction, converts the image data to text data that identifies text within the contractual document, and receives preferences information for a recipient of the offer. The device identifies key terms within the contractual document by using term identification to analyze the text. The key terms may include a first key term that identifies subject matter of the proposed transaction and other key terms that are part of the offer. The device determines term scores that correspond to likelihoods of the other key terms being favorable to the recipient by using a data model to analyze the key terms and the preferences information. The device, based on the term scores, generates and provides another device with a recommendation to be used in determining whether the accept the offer.

Abstract: A device may determine a price of a product based on first information concerning attributes of the product, and provide the price for display by a user device. The device may generate first hash values based on the first information, where a particular first hash value is associated with a particular attribute, and generate a first bit-string that includes the plurality of first hash values. The device may generate second hash values based on second information concerning the attributes of the product, where a particular second hash value is associated with the particular attribute. The device may generate a second bit-string that includes the second hash values, and determine a change to the particular attribute based on the first bit-string and the second bit-string. The device may determine a new price of the product based on the change, and provide the new price for display by the user device.

Abstract: A device may determine that a user device, associated with a user, and a first object for comparison are within a threshold proximity of one another. The device may communicate with the user device to obtain a comparison profile, associated with the user, based on determining that the user device and the first object are within the threshold proximity of one another. The device may identify, based on the comparison profile, a set of desired attributes. The device may identify, based on the comparison profile, a set of attribute categories to be used to compare the first object and the set of desired attributes. The device may determine a first set of attributes of the first object for the set of attribute categories. The device may present, for display, information that identifies one or more attributes of the first set of attributes or the set of desired attributes.

Abstract: Various embodiments are generally directed to techniques of overlaying a virtual object on a physical object in augmented reality (AR). A computing device may receive one or more images of the physical object, perform analysis on the images (such as image segmentation) to generate a digital outline, and determine a position and a scale of the physical object based at least in part on the digital outline. The computing device may configure (e.g., rotate, scale) a 3D model of the physical object to match the determined position and scale of the physical object. The computing device may place or overlay a 3D virtual object on the physical object in AR based on a predefined location relation between the 3D virtual object and the 3D model of the physical object, and further, generate a composite view of the placement or overlay.

Abstract: Disclosed are a system and techniques for identity and electronic signature verification that utilizes blockchain technology. An enterprise system enables computing devices to engage the enterprise and prospective users for the purposes of executing a document or a smart contract. Users may obtain a computer application from an enterprise system and may utilize the computer application to retrieve a document or select a smart contract. The identity of all users who execute the document may be verified based on an authentication by a trusted independent system. Information related to the respective signers, the document or smart contract, and the authentication may be stored as transactions in a blockchain. The transactions may be stored in the blockchain under a user's address, a document or smart contract address, or a digital wallet, if available.

Abstract: A device receives an image including image data of a scale model of a vehicle, and processes the image data, with a model, to identify a make, a model, and a year represented by the scale model. The device determines augmented reality (AR) vehicle information based on the make, the model, and the year represented by the scale model of the vehicle, and provides the AR vehicle information to enable a user device to associate the AR vehicle information with the image of the scale model of the vehicle. The device receives an input associated with the AR vehicle information, and determines updated AR vehicle information based on the input associated with the AR vehicle information. The device provides the updated AR vehicle information to enable the user device to associate the updated augmented reality vehicle information with the image of the scale model of the vehicle.

Abstract: Embodiments disclosed herein provide for a system and method for recalibrating an augmented reality experience in mobile devices using a plurality of physical markers. The system and methods provide for realigning the digital representation to the physical world using known physical locations associated with the physical markers that map directly to the digital representation.

Abstract: Techniques for providing indirect local geo-positioning using AR markers are disclosed. A first movable AR marker can be located or found by a computing device. A location of the first movable AR marker can be known and shared with the computing device. The location of the first movable AR marker can be based on distance between the first movable AR marker and a fixed AR marker. A distance to the first movable AR marker can be determined. Based on the known location of the first movable AR marker and the distance to the first movable AR marker from the computing device, an estimate of the location of the computing device can be determined without having line-of-sight (LOS) to the fixed AR marker.

Abstract: According to certain aspects of the disclosure, a computer-implemented method may be used for determining one or more vehicle recommendations. The method may include receiving data pertaining to a user's internet browsing activity. The received data may be indicative of the user's automotive vehicle preferences. The method may include comparing the received data to a collection of stored vehicle qualities. The method also may include identifying, based on the received data and the comparison of the received data to the collection of stored vehicle qualities, a vehicle characteristic of interest to the user. Using the vehicle characteristic of interest, one or more vehicle recommendations may be determined. One or more vehicle recommendations may be communicated to the user.

Abstract: A server device may receive a first request to utilize surplus parking spaces available at one or more locations from a first device associated with an organization having an inventory of vehicles to be stored in the surplus parking spaces. The server device may process, between the organization and one or more parking providers associated with the one or more locations, a transaction allocating the surplus parking spaces to the organization. The server device may receive, from a second device, a second request to use a vehicle in the inventory from a starting location. The server device may determine, from among the surplus parking spaces allocated to the organization, a storage location for the vehicle that differs from the starting location and transmit, to the second device, a notification indicating that the vehicle is ready for use based on the vehicle having been moved to the starting location.

Abstract: A device having extended reality capabilities receives a video feed including one or more video frames depicting an object. The device provides the one or more video frames to a first machine learning model that identifies the object and one or more parts of the object that are depicted in the one or more video frames, and obtains positional tracking information that represents a position and an orientation associated with the object depicted in the one or more video frames relative to a coordinate space. The device identifies a plurality of parts from the one or more parts of the object that are depicted in the one or more video frames and determines, using one or more second machine learning models, information regarding the plurality of parts and information regarding one or more replacement parts.

Abstract: Various embodiments are generally directed to techniques of overlaying a virtual object on a physical object in augmented reality (AR). A computing device may receive one or more images of the physical object, perform analysis on the images (such as image segmentation) to generate a digital outline, and determine a position and a scale of the physical object based at least in part on the digital outline. The computing device may configure (e.g., rotate, scale) a 3D model of the physical object to match the determined position and scale of the physical object. The computing device may place or overlay a 3D virtual object on the physical object in AR based on a predefined location relation between the 3D virtual object and the 3D model of the physical object, and further, generate a composite view of the placement or overlay.

Abstract: A behavioral analytics platform may obtain a first data model that has been trained based on behavior data derived from historical sales data associated with a vendor and receive, from a user device, one or more interactions that request information related to one or more financing terms. The behavioral analytics platform may determine one or more financing preferences for a user of the user device based on a second data model that has been trained based on behavior data derived from the one or more interactions. The behavioral analytics platform may determine, based on the first data model and the second data model, a probability that the user of the user device and the vendor will be able to reach an agreement for an item available to purchase from the vendor and provide intelligence data related to the probability for display.

Abstract: Disclosed are a system and techniques for identity and electronic signature verification that utilizes blockchain technology. An enterprise system enables computing devices to engage the enterprise and prospective users for the purposes of executing a document or a smart contract. Users may obtain a computer application from an enterprise system and may utilize the computer application to retrieve a document or select a smart contract. The identity of all users who execute the document may be verified based on an authentication by a trusted independent system. Information related to the respective signers, the document or smart contract, and the authentication may be stored as transactions in a blockchain. The transactions may be stored in the blockchain under a user's address, a document or smart contract address, or a digital wallet, if available.

Abstract: A device having extended reality capabilities receives a video feed including one or more video frames depicting an object. The device provides the one or more video frames to a first machine learning model that identifies the object and one or more parts of the object that are depicted in the one or more video frames, and obtains positional tracking information that represents a position and an orientation associated with the object depicted in the one or more video frames relative to a coordinate space. The device identifies a plurality of parts from the one or more parts of the object that are depicted in the one or more video frames and determines, using one or more second machine learning models, information regarding the plurality of parts and information regarding one or more replacement parts.

Abstract: A device may determine a price of a product based on first information concerning attributes of the product, and provide the price for display by a user device. The device may generate first hash values based on the first information, where a particular first hash value is associated with a particular attribute, and generate a first bit-string that includes the plurality of first hash values. The device may generate second hash values based on second information concerning the attributes of the product, where a particular second hash value is associated with the particular attribute. The device may generate a second bit-string that includes the second hash values, and determine a change to the particular attribute based on the first bit-string and the second bit-string. The device may determine a new price of the product based on the change, and provide the new price for display by the user device.

Abstract: A device receives image data of a contractual document that includes an offer including terms of a proposed transaction, converts the image data to text data that identifies text within the contractual document, and receives preferences information for a recipient of the offer. The device identifies key terms within the contractual document by using term identification to analyze the text. The key terms may include a first key term that identifies subject matter of the proposed transaction and other key terms that are part of the offer. The device determines term scores that correspond to likelihoods of the other key terms being favorable to the recipient by using a data model to analyze the key terms and the preferences information. The device, based on the term scores, generates and provides another device with a recommendation to be used in determining whether the accept the offer.

Abstract: A computer-implemented method for using a machine-learning trained predictive engine to predict failures includes receiving electronic prior transaction data corresponding to a plurality of prior successful transactions and a plurality of prior unsuccessful transactions, and training a machine learning predictive engine based on the plurality of prior successful transactions and the plurality of prior unsuccessful transactions. Electronic transaction data may be received, the electronic transaction data being associated with a user, an item, and candidate transaction terms, the electronic transaction data being associated with a candidate transaction. The machine learning predictive engine may determine a likelihood of success of the candidate transaction based on the electronic transaction data, and display the likelihood of success of the candidate transaction.