Key Frame Selection Algorithms for Automatic Generation of Panoramic Images from Crowdsourced Geo-tagged Videos

Currently, an increasing number of user-generated videos (UGVs) are being collected – a trend that is driven by the ubiquitous availability of smartphones. Additionally, it has become easy to continuously acquire and fuse various sensor data (e.g., geospatial metadata) together with video to create sensor-rich mobile videos. As a result, large repositories of media contents can be automatically geo-tagged at the fine granularity of frames during video recording. Thus, UGVs have great potential to be utilized in various geographic information system (GIS) applications, for example, as source media to automatically generate panoramic images. However, large amounts of crowdsourced media data are currently underutilized because it is very challenging to manage, browse and explore UGVs.

[1]  Steve Mann,et al.  Virtual bellows: constructing high quality stills from video , 1994, Proceedings of 1st International Conference on Image Processing.

[2]  Kiyoharu Aizawa,et al.  Capturing wide-view images with uncalibrated cameras , 1998, Electronic Imaging.

[3]  Cyrus Shahabi,et al.  MediaQ: mobile multimedia management system , 2014, MMSys '14.

[4]  Frank Nielsen,et al.  Randomized Adaptive Algorithms for Mosaicing Systems , 1998, MVA.

[5]  Dieter Schmalstieg,et al.  Real-time panoramic mapping and tracking on mobile phones , 2010, 2010 IEEE Virtual Reality Conference (VR).

[6]  Allen R. Hanson,et al.  Fast generation of dynamic and multi-resolution 360/spl deg/ panorama from video sequences , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[7]  Richard Szeliski,et al.  Video mosaics for virtual environments , 1996, IEEE Computer Graphics and Applications.

[8]  David Salesin,et al.  Photographing long scenes with multi-viewpoint panoramas , 2006, SIGGRAPH 2006.

[9]  Ying Zhang,et al.  Dynamic Multi-video Summarization of Sensor-Rich Videos in Geo-Space , 2013, MMM.

[10]  Cyrus Shahabi,et al.  GeoCrowd: enabling query answering with spatial crowdsourcing , 2012, SIGSPATIAL/GIS.

[11]  David R. Bull,et al.  Projective image restoration using sparsity regularization , 2013, 2013 IEEE International Conference on Image Processing.

[12]  Naokazu Yokoya,et al.  Generation of high-resolution stereo panoramic images by omnidirectional imaging sensor using hexagonal pyramidal mirrors , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[13]  Chiou-Ting Hsu,et al.  Feature-based video mosaic , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[14]  Shmuel Peleg,et al.  Panoramic mosaics by manifold projection , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[15]  Jiang Yu Zheng.  Digital Route Panoramas , 2003, IEEE Multim..

[16]  Manolis I. A. Lourakis,et al.  SBA: A software package for generic sparse bundle adjustment , 2009, TOMS.

[17]  Mahmood Fathy,et al.  Efficient key frames selection for panorama generation from video , 2011, J. Electronic Imaging.

[18]  Roger Zimmermann,et al.  Viewable scene modeling for geospatial video search , 2008, ACM Multimedia.

[19]  Richard Szeliski,et al.  Creating full view panoramic image mosaics and environment maps , 1997, SIGGRAPH.

[20]  Yu Hen Hu,et al.  Discovering panoramas in web videos , 2008, ACM Multimedia.

[21]  Mahmood Fathy,et al.  Key frames selection into panoramic mosaics , 2009, 2009 7th International Conference on Information, Communications and Signal Processing (ICICS).

[22]  Richard Szeliski,et al.  Efficiently registering video into panoramic mosaics , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.

[23]  Matthieu Guillaumin,et al.  Combining Image-Level and Segment-Level Models for Automatic Annotation , 2012, MMM.