Automatically converting photographic series into video

ABSTRACT

In this paper, we proposed a novel way to browse a series of otogras, which can be regarded as a system exploring the new medium between otogra and video. The scheme exploits the rich content embedded in a single otogra and otograic series. Based on studying the process of a viewer's attention variation on objects or regions of an image, a otogra can be converted into a motion clip. A system named <i>oto2Video</i> was developed to automatically convert a otograic series into a video by simulating camera motions, set to incidental music of the user's choice. For a selected otograic series, an appropriate set of <i>key-frames</i> are determined for each otogra based on soisticated content analytical results. Then camera motion pattern (both the <i>key-frame sequencing</i> scheme and <i>trajectory/speed control</i> strategy) is selected for each otogra to generate a corresponding motion otogra clip. And last, the final output video is rendered by connecting a series of motion otogra clips with specific transitions based on the content of the images on either side, as well as each motion otogra clip is aligned with the selected incidental music based on music content analysis.

REFERENCES

• 1: Samuel Boivin , Andre Gagalowicz, Image-based rendering of diffuse, specular and glossy surfaces from a single image, Proceedings of the 28th annual conference on Computer graphics and interactive techniques, p.107-116, August 2001 [doi>10.1145/383259.383270]
• 2: Hua, X.S., et al. Content-Based oto Slide Show with Incidental Music. In Proceeding of ISCAS 2003.
• 3: Youichi Horry , Ken-Ichi Anjyo , Kiyoshi Arai, Tour into the picture: using a spidery mesh interface to make animation from a single image, Proceedings of the 24th annual conference on Computer graphics and interactive techniques, p.225-232, August 1997 [doi>10.1145/258734.258854]
• 4: Yu-Fei Ma , Hong-Jiang Zhang, Contrast-based image attention analysis by using fuzzy growing, Proceedings of the eleventh ACM international conference on Multimedia, November 02-08, 2003, Berkeley, CA, USA [doi>10.1145/957013.957094]
• 5: Li, X., et al. Blind Image Quality Assessment. Intl. Conf. on Image Processing, New York, USA, 2002,
• 6: Microsoft Plus! Digital Media Edition. http://www.microsoft.com.
• 7: Byong Mok Oh , Max Chen , Julie Dorsey , Frédo Durand, Image-based modeling and photo editing, Proceedings of the 28th annual conference on Computer graphics and interactive techniques, p.433-442, August 2001 [doi>10.1145/383259.383310]
• 8: Whitley, D. A Genetic Algorithm Tutorial. Statistics and Computing, 1994, 4, 64--85.
• 9: Xiao, R., et al. Robust Multi-Pose Face Detection in Images. IEEE Trans. on CSVT, Special Issue on Biometrics, 2003
• 10: Lei Zhang , Longbin Chen , Mingjing Li , Hongjiang Zhang, Automated annotation of human faces in family albums, Proceedings of the eleventh ACM international conference on Multimedia, November 02-08, 2003, Berkeley, CA, USA [doi>10.1145/957013.957090]
• 11: Lei Zhang , Mingjing Li , Hong-Jiang Zhang, Boosting Image Orientation Detection with Indoor vs. Outdoor Classification, Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision, p.95, December 03-04, 2002

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.1 Multimedia Information Systems
          Subjects: Animations

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.10 Vision and Scene Understanding
            Subjects: Representations, data structures, and transforms

General Terms:
Algorithms, Experimentation

Keywords:
attention detection, audio segmentation, face detection, image clustering, image content analysis