Abstract:
A system and method of providing annotated trajectories by receiving image frames from a video camera and determining a location based on the image frames from the video camera. The system and method can further include the steps of determining that the location is associated with a preexisting annotation and displaying the preexisting annotation. Additionally or alternatively, the system and method can further include the steps of generating a new annotation automatically or based on a user input and associating the new annotation with the current location.
Abstract:
What is disclosed is a system and method for enhancing a spatio-temporal resolution of a depth data stream. In one embodiment, time-sequential reflectance frames and time-sequential depth frames of a scene are received. If a temporal resolution of the reflectance frames is greater than the depth frames then a new depth frame is generated based on correlations determined between motion patterns in the sequence of reflectance frames and the sequence of depth frames. The new depth frame is inserted into the sequence of depth frames at a selected time point. If a spatial resolution of the reflectance frames is greater than the depth frames then the spatial resolution of a selected depth frame is enhanced by generating new pixel depth values which are added to the selected depth frame. The spatially enhanced depth frame is then inserted back into the sequence of depth frames.
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:
What is disclosed is a system and method for adaptively reconstructing a depth map of a scene. In one embodiment, upon receiving a mask identifying a region of interest (ROI), a processor changes either a spatial attribute of a pattern of source light projected on the scene by a light modulator which projects an undistorted pattern of light with known spatio-temporal attributes on the scene, or changes an operative resolution of a depth map reconstruction module. A sensing device detects the reflected pattern of light. A depth map of the scene is generated by the depth map reconstruction module by establishing correspondences between spatial attributes in the detected pattern and spatial attributes of the projected undistorted pattern and triangulating the correspondences to characterize differences therebetween. The depth map is such that a spatial resolution in the ROI is higher relative to a spatial resolution of locations not within the ROI.
Abstract:
The present disclosure relates to systems and methods for use in a retail store. An example system includes a mobile base, a printer, an image capture subsystem on the mobile base and coupled to the printer, the image capture system including at least one image capture device and at least one image processor, the image capture device configured to obtain images of items in the retail store, the image processor configured to derive item identification data from the images of items, and a control subsystem coupled to the printer and to the image capture subsystem, where the control subsystem is configured to receive information identifying items requiring signage, acquire item identification data from the image capture subsystem, determine, based on the information identifying items requiring signage and on the item identification data, items requiring signage, and to direct the printer to print signage for the items requiring signage.
Abstract:
A computer-implemented method, system, and computer-readable medium is disclosed for determining an estimated available parking distance for a vehicle via vehicle side detection in one or more image frames from an operational video. The operational video can be acquired from a fixed parking occupancy video camera and can include a field of view associated with a parking region. The method can include obtaining operational video from a fixed parking occupancy video camera; detecting, within a region of interest (ROI) of the one or more image frames from the operational video, a side of one or more vehicles parked in a parking region facing a traffic lane using a trained classifier that is trained to detect the side of the one or more vehicles; and determining an estimated available parking distance based on the side of the one or more vehicles that are detected.
Abstract:
Methods and systems receive an image-processing request relating to user images from a user. Such methods and systems classify the user images into user-request image-element categories. Such methods and systems also retrieve previously stored user-specific preferences for the user-request image-element categories from a computer storage, when the previously stored user-specific preferences for the user-request image-element categories are maintained in the computer storage. However, when the previously stored user-specific preferences for the user-request image-element categories are not maintained in (are absent from) the computer storage, such methods and systems obtain additional user-specific preferences for the user-request image-element categories. Such methods and systems can then processes the image-processing request by altering renditions of the user images according to the previously stored user-specific preferences and/or the additional user-specific preferences.
Abstract:
Methods and systems for developing shelf product location and identification layout for a retail environment. Such an approach can include a mobile base navigable throughout the retail environment, at least one camera mounted on the mobile base acquiring images of aisles, shelving, and product located on the shelving throughout the retail environment; and a computer controlling mobile base movement, tracking mobile base location and orientation, and organizing images acquired by the camera including facing information for product associated with shelving and aisles as images are acquired and input to the computer to generate plane-like panoramas representing inventory, inventory location, and layout of the retail environment.
Abstract:
A method for detecting parking occupancy includes receiving video data from a sequence of frames taken from an associated image capture device monitoring a parking area. The method includes determining at least one candidate region in the parking area. The method includes comparing a size of the candidate region to a size threshold. In response to size of the candidate region meeting and exceeding the size threshold, the method includes determining whether the candidate region includes one of at least one object and no objects. The method includes classifying at least one object in the candidate region as belonging to one of at least two vehicle-types. The method further includes providing vehicle occupancy information to a user.
Abstract:
This disclosure provides an image processing method and system for recognizing barcodes and/or product labels. According to an exemplary embodiment, the method uses a multifaceted detection process that includes both image enhancement of a candidate barcode region and other product label information associated with a candidate barcode region to identify a product label, where the candidate barcode region includes a nonreadable barcode. According to one exemplary application, a store profile is generated based on the identifications of the product labels which are associated with a location of a product within a store.