Adobe, Inc.

Snap Inc.

Joel Richard Brandt

Lubomira A Dontcheva

Hijung Shin

Aseem Agarwala

Dingzeyu Li

Joy Oakyung Kim

Seth John Walker

Xue Bai

Jovan Popović

Cristin Ailidh Fraser

Kim Pascal Pimmel

Justin Salamon

Zhengyang Ma

Kyratso George Karahalios

Xuecong Xu

Pankaj Kumar Nathani

Anh Lan Truong

Ian Anthony Wehrman

Giles Goodwin

Jared Iwata

Timothy Jeewun Ganter

Jui-hsien Wang

David P Simons

James Acquavella

David Tristram

Jesper Storm Bache

Hanieh Deilamsalehy

Haoran Cai

Barkin Aygun

Ian A Wehrman

John N Fitzgerald

Gregory Scott Evans

Li-Yi Wei

Wilmot Li

Stephen Diverdi

Benoit Gerard Ambry

Deepali Aneja

John Nelson

Morgan Dixon

Christopher Nuuja

Morgan Nicole Evans

David R Stein

Stephen W Oney

Amanda Marie Swearngin

Jiaju Ma

Rubaiat Habib

Zachary Platt McCullough

Najika Skyler Halsema Yoo

William Hayes Allen

Haiqing Lu

Embodiments of the present invention provide systems, methods, and computer storage media for a visual and text search interface used to navigate a video transcript. In an example embodiment, a freeform text query triggers a visual search for frames of a loaded video that match the freeform text query (e.g., frame embeddings that match a corresponding embedding of the freeform query), and triggers a text search for matching words from a corresponding transcript or from tags of detected features from the loaded video. Visual search results are displayed (e.g., in a row of tiles that can be scrolled to the left and right), and textual search results are displayed (e.g., in a row of tiles that can be scrolled up and down). Selecting (e.g., clicking or tapping on) a search result tile navigates a transcript interface to a corresponding portion of the transcript.

Visual and text search interface for text-based video editing

Embodiments of the present invention provide systems, methods, and computer storage media for selection of the best image of a particular speaker's face in a video, and visualization in a diarized transcript. In an example embodiment, candidate images of a face of a detected speaker are extracted from frames of a video identified by a detected face track for the face, and a representative image of the detected speaker's face is selected from the candidate images based on image quality, facial emotion (e.g., using an emotion classifier that generates a happiness score), a size factor (e.g., favoring larger images), and/or penalizing images that appear towards the beginning or end of a face track. As such, each segment of the transcript is presented with the representative image of the speaker who spoke that segment and/or input is accepted changing the representative image associated with each speaker.

Speaker thumbnail selection and speaker visualization in diarized transcripts for text-based video

Embodiments of the present invention provide systems, methods, and computer storage media for segmenting a transcript into paragraphs. In an example embodiment, a transcript is segmented to start a new paragraph whenever there is a change in speaker and/or a long pause in speech. If any remaining paragraphs are longer than a designated length or duration (e.g., 50 or 100 words), each of those paragraphs is segmented using dynamic programming to minimize a cost function that penalizes candidate paragraphs based on divergence from a target paragraph length and/or that rewards candidate paragraphs that group semantically similar sentences. As such, the transcript is visualized, segmented at the identified paragraphs.

Transcript paragraph segmentation and visualization of transcript paragraphs

Embodiments of the present disclosure provide, a method, a system, and a computer storage media that provide mechanisms for multimedia effect addition and editing support for text-based video editing tools. The method includes generating a user interface (UI) displaying a transcript of an audio track of a video and receiving, via the UI, input identifying selection of a text segment from the transcript. The method also includes in response to receiving, via the UI, input identifying selection of a particular type of text stylization or layout for application to the text segment. The method further includes identifying a video effect corresponding to the particular type of text stylization or layout, applying the video effect to a video segment corresponding to the text segment, and applying the particular type of text stylization or layout to the text segment to visually represent the video effect in the transcript.

Video editing using transcript text stylization and layout

Display screen or portion thereof with graphical user interface

Embodiments of the present invention provide systems, methods, and computer storage media for identifying candidate boundaries for video segments, video segment selection using those boundaries, and text-based video editing of video segments selected via transcript interactions. In an example implementation, boundaries of detected sentences and words are extracted from a transcript, the boundaries are retimed into an adjacent speech gap to a location where voice or audio activity is a minimum, and the resulting boundaries are stored as candidate boundaries for video segments. As such, a transcript interface presents the transcript, interprets input selecting transcript text as an instruction to select a video segment with corresponding boundaries selected from the candidate boundaries, and interprets commands that are traditionally thought of as text-based operations (e.g., cut, copy, paste) as an instruction to perform a corresponding video editing operation using the selected video segment.

Video segment selection and editing using transcript interactions

Embodiments are directed to a snap point segmentation that defines the locations of selection snap points for a selection of video segments. Candidate snap points are determined from boundaries of feature ranges of the video indicating when instances of detected features are present in the video. In some embodiments, candidate snap point separations are penalized for being separated by less than a minimum duration corresponding to a minimum pixel separation between consecutive snap points on a video timeline. The snap point segmentation is computed by solving a shortest path problem through a graph that models different snap point locations and separations. When a user clicks or taps on the video timeline and drags, a selection snaps to the snap points defined by the snap point segmentation. In some embodiments, the snap points are displayed during a drag operation and disappear when the drag operation is released.

Snap point video segmentation identifying selection snap points for a video

Embodiments are directed to segmentation and hierarchical clustering of video. In an example implementation, a video is ingested to generate a multi-level hierarchical segmentation of the video. In some embodiments, the finest level identifies a smallest interaction unit of the video—semantically defined video segments of unequal duration called clip atoms. Clip atom boundaries are detected in various ways. For example, speech boundaries are detected from audio of the video, and scene boundaries are detected from video frames of the video. The detected boundaries are used to define the clip atoms, which are hierarchically clustered to form a multi-level hierarchical representation of the video. In some cases, the hierarchical segmentation identifies a static, pre-computed, hierarchical set of video segments, where each level of the hierarchical segmentation identifies a complete set (i.e., covering the entire range of the video) of disjoint (i.e., non-overlapping) video segments with a corresponding level of granularity.

Hierarchical segmentation based on voice-activity

Embodiments are directed to techniques for interacting with a hierarchical video segmentation using a metadata panel with a composite list of video metadata. The composite list is segmented into selectable metadata segments at locations corresponding to boundaries of video segments defined by a hierarchical segmentation. In some embodiments, the finest level of a hierarchical segmentation identifies the smallest interaction unit of a video—semantically defined video segments of unequal duration called clip atoms, and higher levels cluster the clip atoms into coarser sets of video segments. One or more metadata segments can be selected in various ways, such as by clicking or tapping on a metadata segment or by performing a metadata search. When a metadata segment is selected, a corresponding video segment is emphasized on the video timeline, a playback cursor is moved to the first video frame of the video segment, and the first video frame is presented.

Interacting with hierarchical clusters of video segments using a metadata panel

Hierarchical segmentation based software tool usage in a video

Embodiments are directed to techniques for interacting with a hierarchical video segmentation using a video timeline. In some embodiments, the finest level of a hierarchical segmentation identifies the smallest interaction unit of a video—semantically defined video segments of unequal duration called clip atoms, and higher levels cluster the clip atoms into coarser sets of video segments. A presented video timeline is segmented based on one of the levels, and one or more segments are selected through interactions with the video timeline. For example, a click or tap on a video segment or a drag operation dragging along the timeline snaps selection boundaries to corresponding segment boundaries defined by the level. Navigating to a different level of the hierarchy transforms the selection into coarser or finer video segments defined by the level. Any operation can be performed on selected video segments, including playing back, trimming, or editing.

Zoom and scroll bar for a video timeline

Hierarchical segmentation of screen captured, screencasted, or streamed video

Growing community of inventors

Venice, CA, United States of America

Joel Richard Brandt