A computer implemented method to present digital images may include storing a digital image in a database and applying a digital image processing technique to the digital image to identify a region of interest of the digital image. The method may also include storing region data that identifies the region of interest of the digital image in the database and receiving a request for information associated with the digital image from a digital device. In response to the request, the method may include providing the digital image and the region data for transmission to the digital device, the digital device configured to adjust a cropping view of the digital image based on the region data to display the region of interest of the digital image.

Various approaches provide for detecting and recognizing text to enable a user to perform various functions or tasks. For example, a user could point a camera at an object with text, in order to capture an image of that object. The camera can be integrated with a portable computing device that is capable of taking the image and processing the image (or providing the image for processing) to recognize, identify, and/or isolate the text in order to send the image of the object as well as recognized text to an application, function, or system, such as an electronic marketplace.

In a vehicular visibility support apparatus, a camera positioned on a front portion that is either the left side or the right side of a vehicle provides an image of a view laterally behind the vehicle including a part of a face of the side of the vehicle as a camera image. An input portion accepts input manipulation to generate an input signal. A control portion trims a desired region in the camera image based on the input signal and provides a trimmed image. The control portion trims the camera image based on: a vertical reference line including a part of the face on the side of the vehicle in a trimmed image before the input manipulation is accepted by the input portion, and a horizontal reference line orthogonal to the vertical reference line; and a direction of movement for change to the desired region inputted to the input portion.

A method for generating a thumbnail of an image, includes: filtering an image to obtain an edge intensity value for each pixel point in the image; sliding a preset rectangular box on the image to perform a search and, at each searched position, calculating a distribution value of information amount in the rectangular box according to the edge intensity values of the pixel points therein; and selecting the rectangular box with the largest distribution value of information amount, and intercepting content of the image corresponding to the selected rectangular box to obtain a thumbnail of the image.

The disclosure relates to a field of plausible timelapse image(s) generation from a single image. A method of generating one or more images of a plausible dayscale timelapse sequence based on a content image using a trained generative neural network and a trained merging neural network is provided. The method includes receiving the content image and one of one or more predefined styles respectively corresponding to times of day to be applied to the content image or style images having styles to be applied to the content image, slicing the content image into n image crops, applying the trained generative neural network with each style to n image crops to obtain n image crops re-stylized according to each style, and merging the re-stylized n image crops for each style with the trained merging neural network to obtain images of a plausible dayscale timelapse sequence for the content image.

An image processing apparatus includes an exaggeration unit configured to perform on an original image including a hand-drawn element an exaggeration process that expands the hand-drawn element to generate an exaggerated image; and a reduction unit configured to reduce the exaggerated image to generate a reduced image of a predetermined size smaller than a size of the original image.

A method, computer-readable storage medium, and device for generating a character model. The method comprises: receiving an input image of a reference subject; processing the input image to generate a normalized image; identifying a set of features present in the normalized image, wherein each feature in the set of features corresponds to a portion of a head or body of the reference subject; for each feature in the set of features, processing at least a portion of the normalized image including the feature by a neural network model corresponding to the feature to generate a parameter vector corresponding to the feature; and combining the parameter vectors output by respective neural network models corresponding to respective features in the set of features to generate a parameterized character model corresponding to reference subject in the input image.

A method for cropping portions of a document comprises displaying an interactive document workspace with a cropping tool on a sub-area thereof, and rendering one or more formatting indicators spatially associated with the sub-area, the indicators indicating formatting properties of the sub-area.

A system and method for training a computer-implemented object classifier includes detecting a foreground visual object within a sub-region of a scene, determining a background model of the sub-region of the scene, the background model representing the sub-region when any foreground visual object is absent from that sub-region, and training the object classifier by computer-implemented machine learning using the background model of the sub-region as a negative training example.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, are described for combining the crop function with zoom, pan and straighten functions as part of a single cropping environment, such that a user can select a portion of an image for cropping, apply zoom, pan and straighten transformations to the selected image portion and then crop the transformed image portion in a single utility. In one aspect, the methods include the actions of receiving user input defining a crop region within a displayed image. The methods also include the actions of displaying a user interface including a cropping panel that is configured to display a subset of the image corresponding to the defined crop region. Further, the methods include the actions of receiving user input requesting to perform at least one of a zoom, rotate or translate operation on the crop region displayed in the cropping panel.