An auto-rotation module having a single-layer neural network on a user device can convert a document image to a monochrome image having black and white pixels and segment the monochrome image into bounding boxes, each bounding box defining a connected segment of black pixels in the monochrome image. The auto-rotation module can determine textual snippets from the bounding boxes and prepare them into input images for the single-layer neural network. The single-layer neural network is trained to process each input image, recognize a correct orientation, and output a set of results for each input image. Each result indicates a probability associated with a particular orientation. The auto-rotation module can examine the results, determine what degree of rotation is needed to achieve a correct orientation of the document image, and automatically rotate the document image by the degree of rotation needed to achieve the correct orientation of the document image.

A method and a platform of generating a document, an electronic device, and a storage medium are provided, which relate to a field of an artificial intelligence technology, in particular to fields of computer vision and deep learning technologies, and may be applied to a text recognition scenario and other scenarios. The method includes: performing a category recognition on a document picture to obtain a target category result; determining a target structured model matched with the target category result; and performing, by using the target structured model, a structure recognition on the document picture to obtain a structure recognition result, so as to generate an electronic document based on the structure recognition result, wherein the structure recognition result includes a field attribute recognition result and a field position recognition result.

The present disclosure describes techniques for facial expression recognition. A first loss function may be determined based on a first set of feature vectors associated with a first set of images depicting facial expressions and a first set of labels indicative of the facial expressions. A second loss function may be determined based on a second set of feature vectors associated with a second set of images depicting asymmetric facial expressions and a second set of labels indicative of the asymmetric facial expressions. The first loss function and the second loss function may be used to determine a maximum loss function. The maximum loss function may be applied during training of a model. The trained model may be configured to predict at least one asymmetric facial expression in a subsequently received image.

A method for analyzing a viewing direction of an electronic component includes inputting a package type and a file image of an electronic component, with the file image having at least one engineering drawing image, and the at least one engineering drawing image being a view of the electronic component in at least one viewing direction; querying and acquiring a viewing direction detection model meeting the package type from a database, with the database storing respective viewing direction detection models of different package types of electronic components; inputting the file image into the viewing direction detection model of the package type to identify the viewing direction of the at least one engineering drawing image; and outputting the viewing direction of the at least one engineering drawing image of the electronic component.

A device, method and system for estimating elevation in images from camera devices is provided. The device detects humans at respective positions in images from a camera device, the camera device having a fixed orientation and fixed focal length. The device estimates, for the humans in the images, respective elevations of the humans, relative to the camera device, at the respective positions based at least on camera device parameters defining the fixed orientation and the fixed focal length. The device associates the respective elevations with the respective positions in the images. The device determines, using the respective elevations associated with the respective positions, a function that estimates elevation in an image from the camera device, using a respective image position coordinate as an input. The device provides the function to a video analytics engine to determine relative real-world positions in subsequent images from the camera device.

A method and a device for determining a placement region of an item are disclosed. The method according to the present disclosure comprises: acquiring position information of an electronic identification at a bar display screen; and determining the placement region of the item according to the position information and a preset mapping relationship.

A control apparatus including an extraction unit configured to extract a subject from an image captured by an image capturing apparatus, an estimation unit configured to estimate a skeleton of the subject extracted by the extraction unit and a control unit configured to control an angle of view of the image capturing apparatus based on a result of the estimation by the estimation unit.

A system receives a first set of points corresponding to an anatomical feature. Each point in the first set of points represents a position in a first frame. The system receives a second set of points corresponding to the anatomical feature. Each point in the second set of points represents a position in a second frame. The system identifies a first subset of the first set of points and determines a first transformation to align the first subset of the first set of points with the second set of points. The first set of points is transformed based on the first transformation. The system identifies a second subset of the first set of points and determines a second transformation to align the first and second subsets of the first set of points with the second set of points. The first set of points are transformed based on the second transformation.

A hand-held or otherwise portable or spatial or temporal performance-based image capture device includes one or more lenses, an aperture and a main sensor for capturing an original main image. A secondary sensor and optical system are for capturing a reference image that has temporal and spatial overlap with the original image. The device performs an image processing method including capturing the main image with the main sensor and the reference image with the secondary sensor, and utilizing information from the reference image to enhance the main image. The main and secondary sensors are contained together within a housing.

The present disclosure is directed toward systems and methods that efficiently and effectively generate an enhanced document image of a displayed document in an image frame captured from a live image feed. For example, systems and methods described herein apply a document enhancement process to a displayed document in an image frame that result in an enhanced document image that is cropped, rectified, un-shadowed, and with dark text against a mostly white background. Additionally, systems and method described herein determine whether a stored digital content item includes a displayed document. In response to determining that a stored digital content item does include a displayed document, systems and methods described herein generate an enhanced document image of a displayed document included in the stored digital content item.