Keyframe presentation for browsing of user-generated videos on map interfaces

Hao, Jialei; Wang, Guanfeng; Seo, Beomjoo; Zimmermann, Roger

doi:10.1145/2072298.2071926

Cited by 13 publications

(19 citation statements)

References 6 publications

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“…We empirically determine the number of clusters, such that up to K = 2 N/2 clusters are produced for N video segments. To evaluate if the clusters contain representative scenes among the input videos, we compare our results with an existing method [Hao et al 2011] which aims to detect the points-of-interest (POI) from videos by analyzing the geographic meta-data recorded in conjunction with the videos, rather than the video content itself. We apply this method to the same video dataset used in this study and the following POIs are found.…”

Section: Aesthetics-guided Multivideo Summarizationmentioning

confidence: 99%

Aesthetics-Guided Summarization from Multiple User Generated Videos

Zhang

Zimmermann

2015

ACM Trans. Multimedia Comput. Commun. Appl.

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In recent years, with the rapid development of camera technology and portable devices, we have witnessed a flourish of user generated videos, which are gradually reshaping the traditional professional video oriented media market. The volume of user generated videos in repositories is increasing at a rapid rate. In today's video retrieval systems, a simple query will return many videos which seriously increase the viewing burden. To manage these video retrievals and provide viewers with an efficient way to browse, we introduce a system to automatically generate a summarization from multiple user generated videos and present their salience to viewers in an enjoyable manner. Among multiple consumer videos, we find their qualities to be highly diverse due to various factors such as a photographer's experience or environmental conditions at the time of capture. Such quality inspires us to include a video quality evaluation component into the video summarization since videos with poor qualities can seriously degrade the viewing experience. We first propose a probabilistic model to evaluate the aesthetic quality of each user generated video. This model compares the rich aesthetics information from several well-known photo databases with generic unlabeled consumer videos, under a human perception component indicating the correlation between a video and its constituting frames. Subjective studies were carried out with the results indicating that our method is reliable. Then a novel graph-based formulation is proposed for the multi-video summarization task. Desirable summarization criteria is incorporated as the graph attributes and the problem is solved through a dynamic programming framework. Comparisons with several state-of-the-art methods demonstrate that our algorithm performs better than other methods in generating a skimming video in preserving the essential scenes from the original multiple input videos, with smooth transitions among consecutive segments and appealing aesthetics overall.

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Section: Aesthetics-guided Multivideo Summarizationmentioning

confidence: 99%

Aesthetics-Guided Summarization from Multiple User Generated Videos

Zhang

Zimmermann

2015

ACM Trans. Multimedia Comput. Commun. Appl.

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Section: Challenges and Related Workmentioning

confidence: 99%

“…[6,14] present user-generated videos that relate to geographic areas in a map interface. Their focus is on the automatic selection of keyframes to represent the videos, and the determination of the location to place them on the maps [6]. So they emphasize hotspots that are shot in the videos in front of the shooting spot, along their trajectories, but in regular videos [14].…”

Section: Challenges and Related Workmentioning

confidence: 99%

Sharing and navigating 360° videos and maps in sight surfers

Noronha

Álvares

Chambel

2012

Proceeding of the 16th International Academic MindTrek Conference

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Video allows to capture and present events and scenarios with great authenticity, realism and emotional impact, and it is becoming a pervasive medium; while increasingly users are enjoying and technology is supporting, capturing, sharing and accessing videos shot from their perspectives and experiences. 360º video allows to capture the image all around towards more immersive experiences, while hypervideo supports structuring and navigation of video and related information, and technology for capturing 360º video and its trajectory are becoming more accessible to the users, allowing to support more powerful video user experiences.In this paper, we identify main challenges and describe the design and user evaluation of Sight Surfers, an interactive web application for the visualization and navigation of georeferenced 360º hypervideos, with the aim to potentiate ways to create and engage in novel forms of entertainment, culture and even art. Usability results were very encouraging and users enjoyed and would like to use Sight Surfers.

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“…These geographically described (i.e., georeferenced) media data contain significant information about the region where they were captured and can be effectively processed in various GIS applications, e.g., for visual navigation and geospace queries. Both camera position and orientation sensor data are also employed by various GIS and social media applications such as street navigation systems [5], photo organization and management [3], video indexing and tagging [6,13], video summarizations [17,4], video encoding complexity reductions [2,15], and others.…”

Section: Introductionmentioning

confidence: 99%

Orientation data correction with georeferenced mobile videos

Wang

Yin

Seo

et al. 2013

Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

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Similar to positioning data, camera orientation information has become a powerful contextual feature utilized by a number of GIS and social media applications. Such auxiliary information facilitates higher-level semantic analysis and management of video assets in such applications, e.g., video summarization and video indexing systems. However, it is problematic that raw sensor data collected from current mobile devices is often not accurate enough for subsequent geospatial analysis. To date, an effective orientation data correction system for mobile video content has been lacking. Here we present a content-based approach that improves the accuracy of noisy orientation sensor measurements generated by mobile devices in conjunction with video acquisition. Our preliminary experimental results demonstrate significant accuracy enhancements which benefit upstream sensor-aided GIS applications to access video content more precisely.

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Keyframe presentation for browsing of user-generated videos on map interfaces

Cited by 13 publications

References 6 publications

Aesthetics-Guided Summarization from Multiple User Generated Videos

Aesthetics-Guided Summarization from Multiple User Generated Videos

Sharing and navigating 360° videos and maps in sight surfers

Orientation data correction with georeferenced mobile videos

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