Locations and presentation orders of objects of interest (e.g., speech bubbles) in digital graphic novel content are identified such that expanded versions of the objects of interest can be presented to a reader. Specifically, digital graphic novel content is received and locations of interest regions (e.g., rectangular text regions of speech bubbles) in the content are identified by applying a machine-learned model to the content. Locations and presentation orders of objects of interest in the digital graphic novel content are identified based on the identified locations of the interest regions. The digital graphic novel content and presentation metadata including the locations and presentation orders of the objects of interest are provided to a reading device such that expanded versions of the objects of interest are presented to the user in accordance with the presentation metadata.

Provided is a computer-implemented method for authenticating an identification document. The method includes determining, with at least one processor, whether image data associated with the identification document has at least one predetermined indicia. In response to determining that the image data has the at least one predetermined indicia, the method includes determining whether the at least one predetermined indicia corresponds to at least one invalidation mark on the identification document, and, in response to determining that the at least one predetermined indicia corresponds to the at least one invalidation mark, determining, that the identification document is invalid. In response to determining that the identification document is invalid, the method includes preventing or causing the prevention of at least one action from being performed. A system and computer program product for authenticating identification documents are also disclosed.

Examples of methods for fiducial pattern detection are described herein. In some examples, a method may include detecting fiducial pattern subsets in image subsets of an image of an object. In some examples, the method may also include selecting a first image subset that includes a largest first fiducial pattern subset. In some examples, the method may further include extending the first fiducial pattern subset from the first image subset to a neighboring second image subset.

A method is provided to using a machine learning model to predict lane geometry where incorrect or missing lane line geometry is detected. Methods may include: receiving a representation of lane line geometry for one or more roads of a road network; identifying an area within the representation including broken lane line geometry; generating a masked area of the area within the representation including the broken lane line geometry; processing the representation with the masked area through an inpainting model, where the inpainting model includes a generator network, where the representation is processed through the generator network which includes dilated convolution layers for inpainting of the masked area with corrected lane line geometry in a corrected representation; and updating a map database to include the corrected lane line geometry in place of the area including the broken lane line geometry based on the corrected representation.

Systems and methods that provide accessible guidance to users when they are attempting to capture images of an object are disclosed. The accessible guided image capture system evaluates a set of images captured by a capturing device to identify attributes of an object, such as edges, sides, corners, and so on. The accessible guided image capture system uses the identified object attributes to identify a direction in which the mobile device is to be repositioned relative to the object in order to capture better images of the object. The accessible guided image capture system can then use the computed direction to transmit a set of instructions (e.g., haptic signals) to enable the repositioning of the capturing device relative to the object.

Systems and methods for performing long-term kinematic tracking of an animal subject are provided. Chronically-affixed motion capture markers including a tissue engaging feature and a reflective marker are described, the motion capture markers enabling long-term motion capture recording of an animal subject. A method of determining a three-dimensional pose of a subject using a trained statistical model configured to generate landmark position data associated with the three-dimensional pose of the animal subject. The method includes using projective geometry to generate three-dimensional image volumes as input to the trained statistical model. Further, a method for profiling a subject’s physical behavior over a period of time by applying clustering to information indicative of movement of the subject over the period of time is described.

The present invention is a collation/retrieval system collating a product manufactured by or delivered from a producer or a distributor with a product to be collated comprising: a storage unit that stores an image feature of a predetermined collation area of the product determined in advance at a position relative to a reference section common in every product; a to-be-collated product feature extraction unit that receives an image of the product to be collated and detecting the reference section of the product from the received image to extract an image feature of the collation area determined by reference to the reference section; and a collation unit that collates the stored image feature with the image feature of the collation area of the product to be collated.

In general, techniques are described for a personal protective equipment (PPE) management system (PPEMS) that uses images of optical patterns embodied on articles of personal protective equipment (PPEs) to identify safety conditions that correspond to usage of the PPEs. In one example, an article of personal protective equipment (PPE) includes a first optical pattern embodied on a surface of the article of PPE; a second optical pattern embodied on the surface of the article of PPE, wherein a spatial relation between the first optical pattern and the second optical pattern is indicative of an operational status of the article of PPE.

Disclosed are an image processing method and apparatus, an electronic device and a computer-readable storage medium. The method comprises: acquiring a video image; when a preset target is detected in the video image, superimposing a foreground sticker on a target image corresponding to the preset target; and when a preset action of the preset target in the video image is detected, generating a screen special effect, in the embodiments of the present disclosure, a video image is acquired, when a preset target is detected in the video image, a foreground sticker is superimposed on a target image corresponding to the preset target, and when a preset action of the preset target in the video image is detected, a screen special effect is generated, such that a screen special effect for the preset action of the preset target can be realized.

The present invention relates to a method for authenticating a document comprising at least one line of anti-counterfeit patterns spaced from each other, the positions of the anti-counterfeit patterns being random, and a partial anti-counterfeit pattern being provided at an edge line of said document, the method comprising the following steps of:

receiving a digital image of said document, said digital image comprising said partial anti-counterfeit pattern in a first edge area corresponding to said edge line;

selecting said first edge area;

copy-pasting said first edge area adjacent to a second edge area of the digital image to generate a combined digital image, said second edge area being opposite to said first edge area, wherein content, which is comprised in said second edge area and located on the same line as said partial anti-counterfeit pattern, and said partial anti-counterfeit pattern jointly form a combined pattern;

authenticating said document by taking into account said combined pattern.