A computer-implemented method for generating a feature descriptor for a location in an image for use in performing descriptor matching in analysing the image, the method comprising determining a set of samples characterising a location in an image by sampling scale-space data representative of the image, the scale-space data comprising data representative of the image at a plurality of length scales; and generating a feature descriptor in dependence on the determined set of samples.

A method, apparatus and computer program product identify objects of interest within images. In a method, the method receives one or more images generated by an image capture device that is configured to be relocated. The method also receives information regarding an estimated location of the image capture device. Based upon a representation of a respective image of the one or more images and respective representations of a plurality of reference images, the method identifies one or more reference images that are associated with the estimated location. The method also identifies an object of interest within the respective image generated by the image capture device based upon respective digital signatures of one or more objects of interest and at least some context associated with the one or more objects of interest that are depicted by the one or more reference images that have been identified.

A method, apparatus and computer program product train a signature encoding module and a query processing module. In a method, at least one of the signature encoding module and the query processing module is trained by providing the signature encoding module with a reference image containing a particular object of interest that is marked therewithin. The method generates a digital signature of the object of interest and at least some context associated therewith and provides the query processing module with a query image and the digital signature representing the object of interest and at least some of the context associated therewith. The method additionally identifies the object of interest within the query image based upon the digital signature and modifies at least one of the signature encoding module or the query processing module based upon a qualitative or quantitative difference between the objects of interest identified within the query image and marked in the reference image.

The present disclosure provides an age recognition method, a non-transitory computer-readable storage medium, and an electronic device. The method includes extracting feature points of a face in an image, preprocessing the image to extract global features of the face, extracting local features of the face based on the feature points, determining an age feature of the face according to the global features and the local features, and inputting the age feature into a pre-trained age recognition model to obtain an age value corresponding to the face in the image.

A path and/or orientation of object approaching an athlete is tracked using two or more cameras. At least two sets of images of the object are obtained using at least two different cameras having different positions. Motion regions within images are identified, and candidate locations in 2D space of the object are identified within the motion region(s). Based thereon, a probable location in 3D space of the identifiable portion is identified, for each of a plurality of instants during which the object was approaching. A piecewise 3D trajectory of at least the identifiable portion of the object is approximated from the probable locations in 3D space of the object for multiple instants during which the object was approaching the athlete. A graphical representation of the 3D trajectory of the object is incorporated into at least one of the sets of images.

An electronic device is provided. The electronic device includes a display, a processor functionally connected with the display, and a memory functionally connected with the processor. The memory stores instructions configured to, when executed, enable the processor to display a first image through the display, display one or more second images through the display while displaying the first image, select a third image from among the one or more second images, identify a value of at least one property of the third image, generate a filter for applying the value of the at least one property to an image, apply the value of the at least one property to the first image using the filter, display the first image, to which the value of the at least one property is applied, through the display, and store the filter in the memory.

Systems, devices, media, and methods are presented for segmenting an image of a video stream with a client device, identifying an area of interest, generating a modified area of interest within one or more image, identifying a first set of pixels and a second set of pixels, and modifying a color value for the first set of pixels.

Embodiments of the present disclosure provide methods, apparatus, systems, and computer program products for using an image of an integrated circuit (IC) including a plurality of cells to locate one or more target cells within the IC. Accordingly, in various embodiments, a footprint for each cell of the plurality of cells is encoded to transform the image of the IC into a two-dimensional string matrix. A string search algorithm is then applied on each encoded dopant region found in the two-dimensional string matrix using an encoded target layout cell to identify one or more candidate regions of interest within the image. Finally, a mask window is slid over each candidate region of interest while performing matching using match criteria to identify any target cells in the one or more target cells that are located within the candidate region of interest.

Systems and methods are provided for multi-schema analysis of patient specific anatomical features from medical images. The system may receive medical images of a patient and metadata associated with the medical images indicative of a selected pathology, and automatically classify the medical images using a segmentation algorithm. The system may use an anatomical feature identification algorithm to identify one or more patient specific anatomical features within the medical images by exploring an anatomical knowledge dataset. A 3D surface mesh model may be generated representing the one or more classified patient specific anatomical features, such that information may be extracted from the 3D surface mesh model based on the selected pathology. Physiological information associated with the selected pathology for the 3D surface mesh model may be generated based on the extracted information.

A computer-implemented method for searching a product corresponding to a query from a customer. The method includes: embedding the query to obtain a query embedding; retrieving product information having a product text and a product image; embedding the product text to obtain a product text embedding, embedding the product image to obtain a product image embedding, and combining the product text embedding and the product image embedding to obtain a product embedding, where the product image embedding has a same format as the product text embedding; subjecting the query embedding and the product embedding to a transformer to determine whether the query and the product are relevant; and providing the product as a search result of the query when the query and the product are relevant.