Evolving video skims into useful multimedia abstractions

Christel, Michael G.; Smith, Michael A.; Taylor, Colin; Winkler, David B.

doi:10.1145/274644.274670

Cited by 148 publications

(97 citation statements)

References 15 publications

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“…Many browsing tools, with better interaction means than provided by a typical video player, have been presented in the literature (for a detailed review see [29]). While many of them are advanced navigation methods (e.g., [7,8]), extended video players (e.g., [10,14,18]) or enhanced video content visualizations [6], some are highly sophisticated browsing tools (e.g., [1,25,30]). These sophisticated tools provide very specific interfaces and advanced interaction methods, such as combined mouse/keyboard interaction for 3D navigation, table-of-content navigation in videos, navigation trees and spatial interaction (e.g., [12,13,22,23,26,28]).…”

Section: Introductionmentioning

confidence: 99%

The Video Browser Showdown: a live evaluation of interactive video search tools

Schoeffmann

Ahlström

Bailer

et al. 2013

Int J Multimed Info Retr

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The Video Browser Showdown evaluates the performance of exploratory video search tools on a common data set in a common environment and in presence of the audience. The main goal of this competition is to enable researchers in the field of interactive video search to directly compare their tools at work. In this paper we present results from the second Video Browser Showdown (VBS2013) and describe and evaluate the tools of all participating teams in detail. The evaluation results give insights on how exploratory video search tools are used and how they perform in direct compari- son. Moreover, we compare the achieved performance to results from another user study where 16 participants employed a standard video player to complete the same tasks as performed in VBS2013. This comparison shows that the sophisticated tools enable better performance in general but for some tasks common video players provide similar performance and could even outperform the expert tools. Our results highlight the need for further improvement of professional tools for interactive search in videos.

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Section: Introductionmentioning

confidence: 99%

The Video Browser Showdown: a live evaluation of interactive video search tools

Schoeffmann

Ahlström

Bailer

et al. 2013

Int J Multimed Info Retr

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“…A formal study was conducted to investigate the importance of aligning the audio with visuals from the same area of the video, and the utility of different sorts of skims as informative summaries 22 . The experimental procedure had each subject experience each treatment in a Latin Square design to counterbalance the ordering/learning effects, i.e., it was a within-subjects design.…”

Section: Temporal Surrogates: Storyboards With Text and Video Skimsmentioning

confidence: 99%

“…• NEW: a new skim, outlined here but discussed in more detail in the study paper 22 • RND: same audio as NEW but with reordered video to test synchronization effects…”

Section: Temporal Surrogates: Storyboards With Text and Video Skimsmentioning

confidence: 99%

Evaluation and user studies with respect to video summarization and browsing

Christel

2006

SPIE Proceedings

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The Informedia group at Carnegie Mellon University has since 1994 been developing and evaluating surrogates, summary interfaces, and visualizations for accessing digital video collections containing thousands of documents, millions of shots, and terabytes of data. This paper surveys the Informedia user studies that have taken place through the years, reporting on how these studies can provide a user pull complementing the technology push as automated video processing advances. The merits of discount usability techniques for iterative improvement and evaluation are presented, as well as the structure of formal empirical investigations with end users that have ecological validity while addressing the human computer interaction metrics of efficiency, effectiveness, and satisfaction. The difficulties in evaluating video summarization and browsing interfaces are discussed. Lessons learned from Informedia user studies are reported with respect to video summarization and browsing, ranging from the simplest portrayal of a single thumbnail to represent video stories, to collections of thumbnails in storyboards, to playable video skims, to video collages with multiple synchronized information perspectives.

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“…Automatic Speech Recognition (ASR) technology has been developed to turn audio into text (Christel et al, 1998) and to provide textual description of the video content. Even though the quality of the ASR transcript is usually not as good as the human generat ed video description, they are still the primary data resource for shot level video retrieval systems (Mezaris et al., 2005;Wildemuth et al, 2004;Amir et al, 2004;Heesch et al, 2004;Cooke et al, 2004).…”

Section: Related Researchmentioning

confidence: 99%

“…Temporal neighbor browsing allows users to navigate around the selected sample s hot keyframe (a single frame that is representative of the content of a shot) from a text query returns. Potential relevant shots may appear just before or after the sample one due to the asynchronous of the visual content and its related transcript (Christel, et al, 1998). Mezaris et al (2004) noted that a visual similarity re-search using a sample picked keyframe is a good design for retrieval.…”

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confidence: 99%

Semantic visual features in content‐based video retrieval

2006

Proc of Assoc for Info

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A new semantic visual features (e.g., car, mountain, and fire) navigation technology is proposed to improve the effectiveness of video retrieval. Traditional temporal neighbor browsing technology allows users to navigate temporal neighbors of a selected sample frame to find additional matches, while semantic visual feature browsing enables users to navigate keyframes that have similar features to the selected sample frame. A pilot evaluation was conducted to compare the effectiveness of three video retrieval designs that support 1) temporal neighbor browsing; 2) semantic visual feature browsing; and 3) fused browsing which is a combination of both temporal neighbor and semantic visual feature browsing. Two types of searching tasks: visual centric and non-visual centric tasks were applied. Initial results indicated that the semantic visual feature browsing system was more efficient for non-visual centric tasks. IntroductionAccess to digital video from news sources such as CNN, MSNBC, or ABC has become commonplace. To make digital multimedia resource discovery and search more convenient, multimedia digital libraries are being developed for research and education.Increasingly, students or instructors are consulting video col lections in search of video shots within larger video "documents" to be used in their projects or lectures. Viewing all videos in full length to find the desired video shots may be feasible for a small collection, but can be very time intensive for a large collection. The ability to search within individual videos, much in the same way that full text searching allows users to search for content instead of their bibliographic surrogates, would g reatly increase access to video content. Recent research on content-based video retrieval indicated that initially performing a text-based query and subsequently proceeding with neighbor or visual similarity browsing proved to be an effective retrieval strategy (Wildemuth et al., 2003;Heesch et al., 2004;Mezaris et al., 2004 ; Amir et al., 2005). Human beings are usually good at pattern recognition through navigation. A retrieval system supporting navigation functions would provide users additional means for content rel ated searching tasks.In this paper we propose a new video content browsing techniqu e: semantic visual feature browsing. Our purpose is to evaluate its effectiveness as compared to traditional temporal neighbor browsing technique for two types of retrieval tasks: visual centric tasks and non-visual centric tasks. After the introduction of related research, a description of the semantic visual feature browsing algorithm will be given. The user interface of a prototype web-based video retrieval system that supports semantic visual feature browsing will be then illustrated. Finally, the methodology of a pilot user study and some initial results from the study will be presented, fol lowed by a brief discussion. Related ResearchVideo retrieval in the context of a digital library has only recently begun to be studied from a research perspective...

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Evolving video skims into useful multimedia abstractions

Cited by 148 publications

References 15 publications

The Video Browser Showdown: a live evaluation of interactive video search tools

The Video Browser Showdown: a live evaluation of interactive video search tools

Evaluation and user studies with respect to video summarization and browsing

Semantic visual features in content‐based video retrieval

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