Abstract:
A method includes receiving a user input (e. g., a one-touch user input), performing segmentation to generate multiple candidate regions of interest (ROIs) in response to the user input, and performing ROI fusion to generate a final ROI (e. g., for a computer vision application). In some cases, the segmentation may include motion-based segmentation, color-based segmentation, or a combination thereof. Further, in some cases, the ROI fusion may include intraframe (or spatial) ROI fusion, temporal ROI fusion, or a combination thereof.
Abstract:
A method for picture processing is described. A first tracking area is obtained. A second tracking area is also obtained. The method includes beginning to track the first tracking area and the second tracking area. Picture processing is performed once a portion of the first tracking area overlapping the second tracking area passes a threshold.
Abstract:
A method for detecting and tracking a target object is described. The method includes performing motion-based tracking for a current video frame by comparing a previous video frame and the current video frame. The method also includes selectively performing object detection in the current video frame based on a tracked parameter.
Abstract:
A method for determining a region of an image is described. The method includes presenting an image of a scene including one or more objects. The method also includes receiving an input selecting a single point on the image corresponding to a target object. The method further includes obtaining a motion mask based on the image. The motion mask indicates a local motion section and a global motion section of the image. The method further includes determining a region in the image based on the selected point and the motion mask.
Abstract:
A method performed by an electronic device is described. The method includes determining a local motion pattern by determining a set of local motion vectors within a region of interest between a previous frame and a current frame. The method also includes determining a global motion pattern by determining a set of global motion vectors between the previous frame and the current frame. The method further includes calculating a separation metric based on the local motion pattern and the global motion pattern. The separation metric indicates a motion difference between the local motion pattern and the global motion pattern. The method additionally includes tracking an object based on the separation metric.
Abstract:
A method of processing data includes receiving, at a computing device, data representative of an image captured by an image sensor. The method also includes determining a first scene clarity score. The method further includes determining whether the first scene clarity score satisfies a threshold, and if the first scene clarity score satisfies the threshold, determining a second scene clarity score based on second data extracted from the data.
Abstract:
Disclosed is a method and apparatus for biometric based media data sharing. The method may include initiating, in a first device, biometric data capture of a user based, at least in part, on playback of media data by the first device. The method may also include determining that captured biometric data of the user does not correspond with biometric data associated with an authorized user of the first device. Furthermore, the method may also include in response to a failure to match the captured biometric data by the first device, establishing that the user is an authorized user of a second device based, at least in part, on the captured biometric data. The method may also include sharing the media data with the second device.
Abstract:
A method of image retrieval includes obtaining information identifying a plurality of selected objects and selecting one among a plurality of candidate geometrical arrangements. This method also includes, by at least one processor, and in response to the selecting, identifying at least one digital image, among a plurality of digital images, that depicts the plurality of selected objects arranged according to the selected candidate geometrical arrangement.
Abstract:
A method for image scanning by an electronic device is described. The method includes obtaining an image pyramid including a plurality of scale levels and at least a first pyramid level for a frame. The method also includes providing a scanning window. The method further includes scanning at least two of the plurality of scale levels of the frame at a plurality of scanning window locations. A number of scanning window locations is equal for each scale level of the at least two scale levels of the first pyramid level.
Abstract:
A method of generating a temporal saliency map is disclosed. In a particular embodiment, the method includes receiving an object bounding box from an object tracker. The method includes cropping a video frame based at least in part on the object bounding box to generate a cropped image. The method further includes performing spatial dual segmentation on the cropped image to generate an initial mask and performing temporal mask refinement on the initial mask to generate a refined mask. The method also includes generating a temporal saliency map based at least in part on the refined mask.