A method, a device, and computer-readable medium are provided for verifying an identity of a user, which pertains to computer technology. In some aspects, the method includes generating a dynamic fingerprint while the user moves a finger along a trajectory of movement in a fingerprint collection area of a fingerprint reader, and comparing the dynamic fingerprint with a referential fingerprint. The method also includes verifying the identity of the user based on the comparison, and generating a report indicating the identity verified.

In some arrangements, product packaging is digitally watermarked over most of its extent to facilitate high-throughput item identification at retail checkouts. Imagery captured by conventional or plenoptic cameras can be processed (e.g., by GPUs) to derive several different perspective-transformed views—further minimizing the need to manually reposition items for identification. Crinkles and other deformations in product packaging can be optically sensed, allowing such surfaces to be virtually flattened to aid identification. Piles of items can be 3D-modelled and virtually segmented into geometric primitives to aid identification, and to discover locations of obscured items. Other data (e.g., including data from sensors in aisles, shelves and carts, and gaze tracking for clues about visual saliency) can be used in assessing identification hypotheses about an item. Logos may be identified and used—or ignored—in product identification. A great variety of other features and arrangements are also detailed.

A book detection apparatus detects a plurality of surface regions on the basis of three-dimensional measurement data that is obtained by a three-dimensional sensor and that falls within a search area, and determines, when a positional relationship between two surface regions among the plurality of surface regions satisfies a positional condition corresponding to a positional relationship between two opened pages of an opened book, the two surface regions as a book region that includes the book.

For an image processing concept, a database is provided in a device, the database comprising data derived from a plurality of frames of a video sequence. A live video feed is obtained from a camera of the device. Information is extracted from a selected image of the live video feed. A search is performed in the database based on the extracted information to retrieve a list of potential frames out of the plurality of frames. An initial pose of the selected image is estimated with respect to one frame of the list of potential frames as a function of the extracted information and the data derived from the one frame. Respective subsequent poses for subsequent images from the live video feed are iteratively estimated, wherein for each of the subsequent images the associated subsequent pose is estimated based on said subsequent image and a respective previously estimated pose. The live video feed is augmented on the device with virtual information based on the estimated initial pose and the subsequent poses.

This document describes techniques and systems that enable a smartphone providing radar-based proxemic context. The techniques and systems use a radar field to accurately determine a user's location and/or physical orientation with respect to an electronic device, such as a smartphone. The radar field also enables the device to receive 3D gestures from the user to interact with the device. The techniques allow the device to provide functionality based on the user's presence and/or orientation, and to appropriately adjust the timing, content, and format of the device's interactions with the user.

A method for detecting a face key point includes: acquiring image data containing a face; detecting a first face key point of the face in the image data; identifying a face type of the face according to the first face key point; performing position correction on the first face key point with reference to the face type; extracting a facial features image containing facial features from the image data based on the first face key point subjected to the position correction; and detecting a second face key point of the face in the facial features image.

According to an embodiment, a paper sheet processing device includes a fluorescence reference member, a light source, and a sensor. The fluorescence reference member is configured to demonstrate fluorescence in accordance with an intensity of excitation light applied. The light source configured to apply the excitation light to the fluorescence reference member and a paper sheet. The sensor configured to take, at a plurality of sensitivity wavelengths, images of irradiation surfaces of the fluorescence reference member and the paper sheet being irradiated with the excitation light. The fluorescence reference member includes a transmittance control element for the excitation light.

A feature image generation apparatus includes circuitry. The circuitry generates, on the basis of a processing target image in which an object appears, a first image showing the object, and generates, as a feature image showing a feature of the object, at least a part of a rotational composite image obtained by composition of a plurality of rotated images obtained by rotating the first image.

A barcode decoding system decodes item identifiers from images of barcodes. The barcode decoding system receives an image of a barcode and rotates the image to a pre-determined orientation. The barcode decoding system also may segment the barcode image to emphasize the portions of the image that correspond to the barcode. The barcode decoding system generates a binary sequence representation of the item identifier encoded in the barcode by applying a barcode classifier model to the barcode image, and decodes the item identifier from the barcode based on the binary sequence representation.

In a method for rotating photos, an orientation flag value of a photo is obtained when the photo is viewed by a user of the electronic device. A rotational value of the photo is determined according to the obtained orientation flag value. The photo is rotated according to the determined rotational value when the photo is displayed on a display screen of the electronic device.