Visual Signatures in Video Visualization

Chen, M.; Hashim, Rathiah; Botchen, Ralf P.; Weiskopf, Daniel; Ertl, Thomas; Thornton, Ian M.

doi:10.1109/tvcg.2006.194

Cited by 48 publications

(25 citation statements)

References 25 publications

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“…A user can understand what happened in the video only with the volume data, although it requires the user to possess a special skill for checking it. Visual Signature [4] is another video visualization system which focuses on the transition of projective regions of moving objects. The differential area of the moving objects forms a colored tube in the horseshoe-shaped volume.…”

Section: Related Workmentioning

confidence: 99%

ActVis: Activity Visualization in Videos

Toyoura

Nishiguchi

Mao

et al. 2013

2013 International Conference on Cyberworlds

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We present ActVis, which is a computer-aided video surveillance system for detecting and visualizing the activation levels of multiple objects in a video. ActVis indicates "something is happening" in a video. A user arranges panels indicating the regions of focusing objects on the video screen. Temporal differential as an activation level in a panel is detected by the system, and a corresponding seek bar representing the level is generated. In general, high-level features, such as body posture or facial direction/expression, cannot be extracted when the target object is partially occluded in video, or it is not human. By employing the temporal differential as a low-level feature and the metaphor of a level meter, our system can notify a user "when something happens." The user can explore highlevel features of the moment. Potential applications of ActVis include the analysis of student activation levels in classroom for professional development of faculty, and observations of wild animals for ecological investigation.

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Section: Related Workmentioning

confidence: 99%

ActVis: Activity Visualization in Videos

Toyoura

Nishiguchi

Mao

et al. 2013

2013 International Conference on Cyberworlds

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“…Daniel and Chen [4] use video visualization to summarize CCTV footage. Chen et al [3] propose to improve visualization using both volume (change) and flow (motion) signatures. Their study show that ordinary people can learn to recognise events based on event signatures in static visualization rather than having to view the entire video content.…”

Section: Related Workmentioning

confidence: 99%

Hierarchical Event Selection for Video Storyboards with a Case Study on Snooker Video Visualization

Parry

Legg

Chung

et al. 2011

IEEE Trans. Visual. Comput. Graphics

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Disclaimer UWE has obtained warranties from all depositors as to their title in the material deposited and as to their right to deposit such material. UWE makes no representation or warranties of commercial utility, title, or fitness for a particular purpose or any other warranty, express or implied in respect of any material deposited.UWE makes no representation that the use of the materials will not infringe any patent, copyright, trademark or other property or proprietary rights. UWE accepts no liability for any infringement of intellectual property rights in any material deposited but will remove such material from public view pending investigation in the event of an allegation of any such infringement. Abstract-Video storyboard, which is a form of video visualization, summarizes the major events in a video using illustrative visualization. There are three main technical challenges in creating a video storyboard, (a) event classification, (b) event selection and (c) event illustration. Among these challenges, (a) is highly application-dependent and requires a significant amount of applicationspecific semantics to be encoded in a system or manually specified by users. This paper focuses on challenges (b) and (c). In particular, we present a framework for hierarchical event representation, and an importance-based selection algorithm for supporting the creation of a video storyboard from a video. We consider the storyboard to be an event summarization for the whole video, whilst each individual illustration on the board is also an event summarization but for a smaller time window. We utilized a 3D visualization template for depicting and annotating events in illustrations. To demonstrate the concepts and algorithms developed, we use Snooker video visualization as a case study, because it has a concrete and agreeable set of semantic definitions for events and can make use of existing techniques of event detection and 3D reconstruction in a reliable manner. Nevertheless, most of our concepts and algorithms developed for challenges (b) and (c) can be applied to other application areas.

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“…Similar to their objectives, we propose a different approach to improve the visualization effectiveness by decreasing the number of time steps for users to visualize for understanding overall data contents and relations. There are also relevant video summaries or visualization techniques [5,6,33], which generally focused on handling images over time.…”

Section: Related Workmentioning

confidence: 99%

Interactive Storyboard for Overall Time-Varying Data Visualization

Shen

2008

2008 IEEE Pacific Visualization Symposium

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Large amounts of time-varying datasets create great challenges for users to understand and explore them. This paper proposes an efficient visualization method for observing overall data contents and changes throughout an entire time-varying dataset. We develop an interactive storyboard approach by composing sample volume renderings and descriptive geometric primitives that are generated through data analysis processes. Our storyboard system integrates automatic visualization generation methods and interactive adjustment procedures to provide new tools for visualizing and exploring time-varying datasets. We also provide a flexible framework to quantify data differences and automatically select representative datasets through exploring scientific data distribution features. Since this approach reduces the visualized data amount into a more understandable size and format for users, it can be used to effectively visualize, represent, and explore a large time-varying dataset. Initial user study results show that our approach shortens the exploration time and reduces the number of datasets that users visualized individually. This visualization method is especially useful for situations that require close observance or are not capable of interactive rendering, such as documentation and demonstration.

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Visual Signatures in Video Visualization

Cited by 48 publications

References 25 publications

ActVis: Activity Visualization in Videos

ActVis: Activity Visualization in Videos

Hierarchical Event Selection for Video Storyboards with a Case Study on Snooker Video Visualization

Interactive Storyboard for Overall Time-Varying Data Visualization

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