Object tracking verification in digital video

    公开(公告)号:US10740925B2

    公开(公告)日:2020-08-11

    申请号:US16115994

    申请日:2018-08-29

    Applicant: Adobe Inc.

    Abstract: Object tracking verification techniques are described as implemented by a computing device. In one example, feature points are selected on and along a boundary of an object to be tracked, e.g., in an initial frame of a digital video, which are referred to as “feature points.” Tracking of the feature points is verified by the computing device between frames. If the feature points have been found to deviate from the object, the feature points are reselected. To verify the feature points, a number of tracked features points in a subsequent frame is compared to a number of feature points used to initiate tracking with respect to a threshold. Based on this comparison, if a number of feature points is “lost” in the subsequent frame that is greater than the threshold, the feature points are reselected for tracking the object in subsequent frames of the video.

    Text enhancement using a binary image generated with a grid-based grayscale-conversion filter

    公开(公告)号:US10699381B2

    公开(公告)日:2020-06-30

    申请号:US15989111

    申请日:2018-05-24

    Applicant: Adobe Inc.

    Abstract: Certain embodiments involve a model for enhancing text in electronic content. For example, a system obtains electronic content comprising input text and converts the electronic content into a grayscale image. The system also converts the grayscale image into a binary image using a grid-based grayscale-conversion filter, which can include: generating a grid of pixels on the grayscale image; determining a plurality of grid-pixel threshold values at intersection points in the grid of pixels; determining a plurality of estimated pixel threshold values based on the plurality of grid-pixel threshold values; and converting the grayscale image into the binary image using the plurality of grid-pixel threshold values and the plurality of estimated pixel threshold values. The system also generates an interpolated image based on the electronic content and the binary image. The interpolated image includes output text that is darker than the input text. The system can then output the interpolated image.

    Systems and techniques for automatic image haze removal across multiple video frames

    公开(公告)号:US10692197B2

    公开(公告)日:2020-06-23

    申请号:US16021186

    申请日:2018-06-28

    Applicant: Adobe Inc.

    Abstract: Computer-implemented systems and methods herein disclose automatic haze correction in a digital video. In one example, a video dehazing module identifies a scene including a set of video frames. The video dehazing module identifies the dark channel, brightness, and atmospheric light characteristics in the scene. For each video frame in the scene, the video dehazing module determines a unique haze correction amount parameter by taking into account the dark channel, brightness, and atmospheric light characteristics. The video dehazing module applies the unique haze correction amount parameters to each video frame and thereby generates a sequence of dehazed video frames.

    VIDEO-BASED DOCUMENT SCANNING
    4.
    发明申请

    公开(公告)号:US20190394350A1

    公开(公告)日:2019-12-26

    申请号:US16017756

    申请日:2018-06-25

    Applicant: ADOBE INC.

    Abstract: Technologies for video-based document scanning are disclosed. The video scanning system may divide a video into segments. A segment has frames with a common feature. For a segment, the video scanning system is configured to rank the frames in the segment, e.g., based on motion characteristics, zoom characteristics, aesthetics characteristics, quality characteristics, etc., of the frames. Accordingly, the system can generate a scan from a selected frame in a segment, e.g., based on the rank of the selected frame in the segment.

    Automatic creation of a group shot image from a short video clip using intelligent select and merge

    公开(公告)号:US10475222B2

    公开(公告)日:2019-11-12

    申请号:US15695924

    申请日:2017-09-05

    Applicant: ADOBE INC.

    Abstract: Systems and techniques are disclosed for automatically creating a group shot image by intelligently selecting a best frame of a video clip to use as a base frame and then intelligently merging features of other frames into the base frame. In an embodiment, this involves determining emotional alignment scores and eye scores for the individual frames of the video clip. The emotional alignment scores for the frames are determined by assessing the faces in each of the frames with respect to an emotional characteristic (e.g., happy, sad, neutral, etc.). The eye scores for the frames are determined based on assessing the states of the eyes (e.g., fully open, partially open, closed, etc.) of the faces in individual frames. Comprehensive scores for the individual frames are determined based on the emotional alignment scores and the eye scores, and the frame having the best comprehensive score is selected as the base frame.

    Video segmentation using predictive models trained to provide aesthetic scores

    公开(公告)号:US10474903B2

    公开(公告)日:2019-11-12

    申请号:US15880077

    申请日:2018-01-25

    Applicant: Adobe Inc.

    Abstract: Systems and methods for segmenting video. A segmentation application executing on a computing device receives a video including video frames. The segmentation application calculates, using a predictive model trained to evaluate quality of video frames, a first aesthetic score for a first video frame and a second aesthetic score for a second video frame. The segmentation application determines that the first aesthetic score and the second aesthetic score differ by a quality threshold and that a number of frames between the first video frame and the second video frame exceeds a duration threshold. The segmentation application creates a video segment by merging a subset of video frames ranging from the first video frame to an segment-end frame preceding the second video frame.

    Automatic creation of media collages

    公开(公告)号:US10692259B2

    公开(公告)日:2020-06-23

    申请号:US15380456

    申请日:2016-12-15

    Applicant: Adobe Inc.

    Abstract: Techniques for automatic creation of media collages are described. In one or more implementations, unwanted frames are identified and removed from items of media content. A media score is then determined for items of media content based on characteristics of an appearance of the items within a plurality of collage templates. A template score is determined for each collage template of the plurality of collage templates by combining the media scores for each media item of the plurality of media items included in a collage template. At least one of the plurality of collage templates is selected based on determined template scores. Then, at least one media collage is outputted based on the selected collage templates.

    TEXT ENHANCEMENT USING A BINARY IMAGE GENERATED WITH A GRID-BASED GRAYSCALE-CONVERSION FILTER

    公开(公告)号:US20190362471A1

    公开(公告)日:2019-11-28

    申请号:US15989111

    申请日:2018-05-24

    Applicant: Adobe Inc.

    Abstract: Certain embodiments involve a model for enhancing text in electronic content. For example, a system obtains electronic content comprising input text and converts the electronic content into a grayscale image. The system also converts the grayscale image into a binary image using a grid-based grayscale-conversion filter, which can include: generating a grid of pixels on the grayscale image; determining a plurality of grid-pixel threshold values at intersection points in the grid of pixels; determining a plurality of estimated pixel threshold values based on the plurality of grid-pixel threshold values; and converting the grayscale image into the binary image using the plurality of grid-pixel threshold values and the plurality of estimated pixel threshold values. The system also generates an interpolated image based on the electronic content and the binary image. The interpolated image includes output text that is darker than the input text. The system can then output the interpolated image.

    Detection of partially motion-blurred video frames

    公开(公告)号:US10482610B2

    公开(公告)日:2019-11-19

    申请号:US15800678

    申请日:2017-11-01

    Applicant: Adobe Inc.

    Abstract: An automated motion-blur detection process can detect frames in digital videos where only a part of the frame exhibits motion blur. Certain embodiments programmatically identify a plurality of feature points within a video clip, and calculate a speed of each feature point within the video clip. A collective speed of the plurality of feature points is determined based on the speed of each feature point. A selection factor is compared to a selection threshold for each video frame. The selection factor is based at least in part on the collective speed of the plurality of feature points. Based on this comparison, at least one video frame from within the video clip is selected. In some aspects, the selected video frame is relatively free of motion blur, even motion blur that occurs in only a part of the image.

    Automatic and intelligent video sorting

    公开(公告)号:US10276213B2

    公开(公告)日:2019-04-30

    申请号:US15602006

    申请日:2017-05-22

    Applicant: ADOBE INC.

    Abstract: Systems and methods disclosed herein provide automatic and intelligent video sorting in the context of creating video compositions. A computing device sorts a media bin of videos in the user's work area based on similarity to the videos included in the video composition being created. When a user selects or includes a particular video on the composition's timeline, the video is compared against the entire video collection to change the display of videos in the media bin. In one example, videos that have similar tags to a selected video are prioritized at the top. Only a subset of frames of each of the videos are used to use to identify video tags. Intelligently selecting tags using a subset of frames from each video rather than using all frames enables more efficient and accurate tagging of videos, which facilitates quicker and more accurate comparison of video similarities.

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