Abstract:
A mobile device detects a moveable foreground object in captured images, e.g., a series of video frames without depth information. The object may be one or more of the user's fingers. The object may be detected by warping one of a captured image of a scene that includes the object and a reference image of the scene without the object so they have the same view and comparing the captured image and the reference image after warping. A mask may be used to segment the object from the captured image. Pixels are detected in the extracted image of the object and the pixels are used to detect the point of interest on the foreground object. The object may then be tracked in subsequent images. Augmentations may be rendered and interacted with or temporal gestures may be detected and desired actions performed accordingly.
Abstract:
Apparatuses and methods for reading a set of images to merge together into a high dynamic range (HDR) output image are described. Images have a respective HDR weight and a respective ghost-free weight. Images are merged together using the weighted average of the set of input images using the ghost-free weight. A difference image is determined based on a difference between each pixel within a HDR output image and each respective pixel within a reference image used to create the HDR output image.
Abstract:
Exemplary methods, apparatuses, and systems for image processing are described. One or more reference images are selected based on image quality scores. At least a portion of each reference image is merged to create an output image. An output image with motion artifacts is compared to a target to correct the motion artifacts of the output image.
Abstract:
A mobile platform efficiently processes image data, using distributed processing in which latency sensitive operations are performed on the mobile platform, while latency insensitive, but computationally intensive operations are performed on a remote server. The mobile platform acquires image data, and determines whether there is a trigger event to transmit the image data to the server. The trigger event may be a change in the image data relative to previously acquired image data, e.g., a scene change in an image. When a change is present, the image data may be transmitted to the server for processing. The server processes the image data and returns information related to the image data, such as identification of an object in an image or a reference image or model. The mobile platform may then perform reference based tracking using the identified object or reference image or model.
Abstract:
Methods, devices, and computer program products for generating high dynamic range images with reduced ghosting and motion blur are disclosed herein. In some aspects, methods of detecting areas of motion blur in an image are disclosed. This detection may be based on either a row-based approach, or a patch-based approach. These approaches may be used to classify images or portions of images as being either blurry or sharp, based upon a threshold value. The threshold value may be determined empirically.