摘要:
A highlight learning technique is provided to detect and identify highlights in sports videos. A set of event models are calculated from low-level frame information of the sports videos to identify recurring events within the videos. The event models are used to characterize videos by detecting events within the videos and using the detected events to generate an event vector. The event vector is used to train a classifier to identify the videos as highlight or non-highlight.
摘要:
An image comprising color pixels with varying illumination is selected. Instances of a repeating pattern in the image are determined. Illumination values for illuminated pixels at locations within instances of the repeating pattern are calculated based on pixel intensities of non-illuminated pixels at corresponding locations in other instances of the repeating pattern. The illumination variation is removed from the illuminated pixels based on the calculated illumination values to produce enhanced pixels. Color from the non-illuminated pixels at the corresponding locations in other instances of the repeating pattern is propagated to the enhanced pixels.
摘要:
Methods and systems for rolling shutter removal are described. A computing device may be configured to determine, in a frame of a video, distinguishable features. The frame may include sets of pixels captured asynchronously. The computing device may be configured to determine for a pixel representing a feature in the frame, a corresponding pixel representing the feature in a consecutive frame; and determine, for a set of pixels including the pixel in the frame, a projective transform that may represent motion of the camera. The computing device may be configured to determine, for the set of pixels in the frame, a mixture transform based on a combination of the projective transform and respective projective transforms determined for other sets of pixels. Accordingly, the computing device may be configured to estimate a motion path of the camera to account for distortion associated with the asynchronous capturing of the sets of pixels.
摘要:
In some instances, an image may have dimensions that do not correspond to a slot to display the image. For example, an image content item may have dimensions that do not correspond to a content item slot. The image may be resized using seam carving to add or remove pixels of the image. A saliency map for the image may be used having saliency scores for each pixel of the image. Evaluation metrics may be used before, during, and after, seam carving to determine whether salient content is affected by the seam carving. In some instances, a seam cost threshold value may be used for adaptive step size during the seam carving. The resized image may then be outputted, such as for an image content item to be served with a resource.
摘要:
An image processing module infers depth from a stereo image pair according to a multi-scale energy minimization process. A stereo image pair is progressively downsampled to generate a pyramid of downsampled image pairs of varying resolution. Starting with the coarsest downsampled image pair, a disparity map is generated that reflects displacement between corresponding pixels in the stereo image pair. The disparity map is then progressively upsampled. At each upsampling stage, the disparity labels are refined according to an energy function. The disparity labels provide depth information related to surfaces depicted in the stereo image pair.
摘要:
An exemplar dictionary is built from exemplars of digital content for determining predictor blocks for encoding and decoding digital content. The exemplar dictionary organizes the exemplars as clusters of similar exemplars. Each cluster is mapped to a label. Machine learning techniques are used to generate a prediction model for predicting a label for an exemplar. The exemplar dictionary is used to encode digital content. Clusters of exemplars are obtained by applying a prediction model to a target block of digital content for encoding. A predictor block is selected for encoding the target block based on frequency of occurrence of exemplars in the clusters. The target block is encoded using the predictor block.
摘要:
An image processing server performs haze-removal from images. Global atmospheric light is estimated and an initial transmission value is estimated. In one embodiment, a solver is applied to an objective function to recover a scene radiance value based on the estimated atmospheric light and estimated transmission value. The scene radiance value is used to construct an image without haze. In a simplified method that avoids using a solver, bilateral filtering is performed on the transmission image in order to construct an image without haze.
摘要:
Methods and systems for processing a video for stabilization and retargeting are described. A recorded video may be stabilized by removing shake introduced in the video, and a video may be retargeted by modifying the video to fit to a different aspect ratio. Constraints can be imposed that require a modified video to contain pixels from the original video and/or to preserve salient regions. In one example, a video may be processed to estimate an original path of a camera that recorded the video, to estimate a new camera path, and to recast the video from the original path to the new camera path. To estimate a new camera path, a virtual crop window can be designated. A difference transformation between the original and new camera path can be applied to the video using the crop window to recast the recorded video from the smooth camera path.
摘要:
Methods and systems for processing an image to facilitate automated object recognition are disclosed. More particularly, an image is processed based on a perceptual grouping for the image (e.g., derived via segmentation, derived via contour detection, etc.) and a geometric-configuration model for the image (e.g., a bounding box model, a constellation, a k-fan, etc.).
摘要:
An image comprising varying illumination is selected. Instances of a repeating pattern in the image is determined. Illumination values for pixels at locations within instances of the repeating pattern are calculated responsive to pixel intensities of pixels at corresponding locations in other instances of the repeating pattern. The varying illumination is removed form the image responsive to the illumination values.