In video production, inserting B-roll is a widely used technique to enrich the story and make a video more engaging. However, determining the right content and positions of B-roll and actually inserting it within the main footage can be challenging, and novice producers often struggle to get both timing and content right. We present B-Script, a system that supports B-roll video editing via interactive transcripts. B-Script has a built-in recommendation system trained on expert-annotated data, recommending users B-roll position and content. To evaluate the system, we conducted a within-subject user study with 110 participants, and compared three interface variations: a timeline-based editor, a transcript-based editor, and a transcript-based editor with recommendations. Users found it easier and were faster to insert B-roll using the transcript-based interface, and they created more engaging videos when recommendations were provided.
Prior research has found that content-focused editing of media, such as transcript-based interfaces, can help people more effectively accomplish video and audio editing @cite_4 @cite_8 @cite_20 @cite_1 @cite_25 @cite_16 . @cite_20 , and more recently, @cite_8 present video editing systems that include video aligned transcript editors to enable more efficient navigation and editing of video.
@cite_4 @cite_8 @cite_1 @cite_16 @cite_25 @cite_20
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Digital video is becoming increasingly ubiquitous. However, editing video remains difficult for several reasons: it is a time-based medium, it has dual tracks of audio and video, and current tools force users to work at the smallest level of detail. Based on interviews with professional video editors, we developed a video editor, called Silver, that uses metadata to make digital video editing more accessible to novices. To help users visualize video, Silver provides multiple views with different semantic content and at different levels of abstraction, including storyboard, editable transcript, and timeline views. Silver offers smart editing operations that help users resolve the inconsistencies that arise because of the different boundaries in audio and video. We conducted a preliminary user study to investigate the effectiveness of the Silver smart editing. Participants successfully edited video after only a short tutorial, both with and without smart editing assistance. Our research suggests several ways in which video editing tools could use metadata to assist users in the reuse and composition of video. We present a set of tools designed to help editors place cuts and create transitions in interview video. To help place cuts, our interface links a text transcript of the video to the corresponding locations in the raw footage. It also visualizes the suitability of cut locations by analyzing the audio visual features of the raw footage to find frames where the speaker is relatively quiet and still. With these tools editors can directly highlight segments of text, check if the endpoints are suitable cut locations and if so, simply delete the text to make the edit. For each cut our system generates visible (e.g. jump-cut, fade, etc.) and seamless, hidden transitions. We present a hierarchical, graph-based algorithm for efficiently generating hidden transitions that considers visual features specific to interview footage. We also describe a new data-driven technique for setting the timing of the hidden transition. Finally, our tools offer a one click method for seamlessly removing 'ums' and repeated words as well as inserting natural-looking pauses to emphasize semantic content. We apply our tools to edit a variety of interviews and also show how they can be used to quickly compose multiple takes of an actor narrating a story. In this paper, we focus on video programs that are intended to disseminate information and knowledge such as news, documentaries, seminars, etc, and present an audiovisual summarization system that summarizes the audio and visual contents of the given video separately, and then integrating the two summaries with a partial alignment. The audio summary is created by selecting spoken sentences that best present the main content of the audio speech while the visual summary is created by eliminating duplicates redundancies and preserving visually rich contents in the image stream. The alignment operation aims to synchronize each spoken sentence in the audio summary with its corresponding speaker's face and to preserve the rich content in the visual summary. A Bipartite Graph-based audiovisual alignment algorithm is developed to efficiently find the best alignment solution that satisfies these alignment requirements. With the proposed system, we strive to produce a video summary that: (1) provides a natural visual and audio content overview, and (2) maximizes the coverage for both audio and visual contents of the original video without having to sacrifice either of them. Video production is a collaborative process in which stakeholders regularly review drafts of the edited video to indicate problems and offer suggestions for improvement. Although practitioners prefer in-person feedback, most reviews are conducted asynchronously via email due to scheduling and location constraints. The use of this impoverished medium is challenging for both providers and consumers of feedback. We introduce VidCrit, a system for providing asynchronous feedback on drafts of edited video that incorporates favorable qualities of an in-person review. This system consists of two separate interfaces: (1) A feedback recording interface captures reviewers' spoken comments, mouse interactions, hand gestures and other physical reactions. (2) A feedback viewing interface transcribes and segments the recorded review into topical comments so that the video author can browse the review by either text or timelines. Our system features novel methods to automatically segment a long review session into topical text comments, and to label such comments with additional contextual information. We interviewed practitioners to inform a set of design guidelines for giving and receiving feedback, and based our system's design on these guidelines. Video reviewers using our system preferred our feedback recording interface over email for providing feedback due to the reduction in time and effort. In a fixed amount of time, reviewers provided 10.9 (σ=5.09) more local comments than when using text. All video authors rated our feedback viewing interface preferable to receiving feedback via e-mail.