Abstract: A store profile generation system includes a mobile base and an image capture assembly mounted on the base. The assembly includes at least one image capture device for acquiring images of product display units in a retail environment. A control unit acquires the images captured by the at least one image capture device at a sequence of locations of the mobile base in the retail environment. The control unit extracts product-related data from the acquired images and generates a store profile indicating locations of products and their associated tags throughout the retail environment, based on the extracted product-related data. The store profile can be used for generating new product labels for a sale in an appropriate order for a person to match to the appropriate locations in a single pass through the store.

Abstract: This disclosure provides a retail environment robotic system including a vertically oriented/scanning LIDAR (Light Detection and Ranging) unit mounted to a mobile base which travels along the aisles of a retail environment such as a store. According to an exemplary embodiment, the LIDAR unit vertically scans product display units along the aisles to generate a depth map associated with detected objects which is further processed to detect missing products, product/shelving tags, shelves, etc.

Abstract: A system to detect and maintain retail store promotional price tags (PPTs) includes a heuristic PPT description extractor module, a heuristic rule deriver module, a store shelf image acquisition system, a barcode locator and recognizer module, and a heuristic PPT classifier module. The heuristic PPT description extractor module extracts heuristic descriptions of PPTs. The heuristic rule deriver module derives a set of heuristic parameters for the PPTs. The barcode locator and recognizer module analyzes images acquired by the store shelf image acquisition system to localize and recognize barcodes. The heuristic PPT description classifier module extracts heuristic attributes from the images acquired by the store shelf image acquisition system using the set of PPT parameters supplied by the heuristic rule deriver module.

Abstract: A store profile generation system includes a mobile base and an image capture assembly mounted on the base. The assembly includes at least one image capture device for acquiring images of product display units in a retail environment. A control unit acquires the images captured by the at least one image capture device at a sequence of locations of the mobile base in the retail environment. The control unit extracts product-related data from the acquired images and generates a store profile indicating locations of products and their associated tags throughout the retail environment, based on the extracted product-related data. The store profile can be used for generating new product labels for a sale in an appropriate order for a person to match to the appropriate locations in a single pass through the store.

Abstract: A system to detect and maintain retail store promotional price tags (PPTs) includes a heuristic PPT description extractor module, a heuristic rule deriver module, a store shelf image acquisition system, a barcode locator and recognizer module, and a heuristic PPT classifier module. The heuristic PPT description extractor module extracts heuristic descriptions of PPTs. The heuristic rule deriver module derives a set of heuristic parameters for the PPTs. The barcode locator and recognizer module analyzes images acquired by the store shelf image acquisition system to localize and recognize barcodes. The heuristic PPT description classifier module extracts heuristic attributes from the images acquired by the store shelf image acquisition system using the set of PPT parameters supplied by the heuristic rule deriver module.

Abstract: This disclosure provides a retail environment robotic system including a vertically oriented/scanning LIDAR (Light Detection and Ranging) unit mounted to a mobile base which travels along the aisles of a retail environment such as a store. According to an exemplary embodiment, the LIDAR unit vertically scans product display units along the aisles to generate a depth map associated with detected objects which is further processed to detect missing products, product/shelving tags, shelves, etc.

Abstract: A computer-based apparatus including a computer including a processor arranged to select a first video regarding a medical condition; create a second video including segments from the first video; transmit the second video for viewing by qualified medical personnel; receive input from the personnel; based on the input confirm accuracy of a first segment or modify a second segment or delete a third segment; create, from the second video, by at least including the first or second segment or deleting the third segment; transmit the third video for viewing by viewers; receive a respective response from each viewer identifying a respective fourth segment of the third video deemed relevant to the medical condition or enjoyable; create a fourth video including at least a portion of the respective fourth segments; and store the fourth video for inclusion in a video regarding the medical condition.

Abstract: A computer-based apparatus including a computer including a processor arranged to select a first video regarding a medical condition; create a second video including segments from the first video; transmit the second video for viewing by qualified medical personnel; receive input from the personnel; based on the input confirm accuracy of a first segment or modify a second segment or delete a third segment; create, from the second video, by at least including the first or second segment or deleting the third segment; transmit the third video for viewing by viewers; receive a respective response from each viewer identifying a respective fourth segment of the third video deemed relevant to the medical condition or enjoyable; create a fourth video including at least a portion of the respective fourth segments; and store the fourth video for inclusion in a video regarding the medical condition.

Abstract: A computer-based method for presenting customized medical information, including: storing, in at least one memory element of at least one computer, computer readable instructions; and executing, using at least one processor for the at least one computer, the computer readable instructions to: receive an input identifying a patient; access electronic medical-related records (EMRRs) for the patient; formulate, based on data in the EMRRs, a query requesting information/input from the patient; transmit the query for display on a first graphical user interface (GUI) device; receive, in response to the query, an input providing the information/input; generate a video including at least one video segment related to the information/input; and transmit the video for display on the first GUI device or on a second GUI device.

Abstract: The present application describes a method for the creation of customized/personalized videos and displays from stock audio/video databases that provide information in a particular subject area. The described method can be applied to many varied fields. For each field, a list of possible applications of customized videos is presented. The customized/personalized videos can be generated from a collection of stock video clips and personal data (i.e. databases) by: 1) collecting and establishing a stock information database 2) collecting personalized information/desired data; 3) parsing, sorting, and indexing stock video segments to meet a particular user's needs; 4) defining a workflow of the contents based on time, location, or cause-effect relationship of contents; and, 5) using video creation tools such as a scripting based approach (e.g., AVISynth©) and/or a playlist interface to stream or assemble the video clips.

Abstract: The present disclosure provides a method of producing a personalized medical record, comprising: incorporating at least a portion of a prerecorded stock tutorial video having stock information and one or more uncompleted segments for inserting personalized medical information onto a single recording medium. The personalized medical information can include personalized health information including vital health statistics. The method combines the at least a portion of the prerecorded stock tutorial video including the stock information on a variety of medical maladies with the personalized medical information. The stock tutorial video can include at least one predeterminable insertion point within the uncompleted segments for inserting the personalized medical information.

Abstract: The present disclosure provides a personalized medical video story, comprising: at least a portion of a prerecorded stock tutorial video having stock information and one or more uncompleted segments for inserting personalized medical information onto a single recording medium. The personalized medical information includes personalized health information including vital health statistics. The at least a portion of the prerecorded stock tutorial video includes stock information on a variety of medical maladies combined with the personalized medical information. The stock tutorial video includes insertion points within the uncompleted segments for inserting the personalized medical information. The personalized medical information at the insertion points is merged with the at least a portion of the prerecorded stock tutorial video for producing at least a portion of the personalized medical video story.