Skip to main content
SpringerLink
Log in

Semantic concept mining in cricket videos for automated highlight generation

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

This paper presents a novel approach towards automated highlight generation of broadcast sports video sequences from its extracted events and semantic concepts. A sports video is hierarchically divided into temporal partitions namely, megaslots, slots, and semantic entities, namely concepts, and events. The proposed method extracts event sequence from video and classifies each sequence into a concept by sequential association mining. The extracted concepts and events within the concepts are selected according to their degree of importance to include those in the highlights. A parameter degree of abstraction is proposed, which gives a choice to the user about how concisely the extracted concepts should be produced for a specified highlight duration. We have successfully extracted highlights from recorded video of cricket match and compared our results with the manually-generated highlights by sports television channel.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

References

  1. Aigrain P, Zhang H, Petkovic D (1996) Representation and retrieval of visual media: a state-of-the-art review. Int J Multimedia Tools Appl 3:179–182

    Article  Google Scholar 

  2. Assfalg J, Bertini M, Colombo C, Bimbo AD (2002) Semantic annotation of sports videos. IEEE Multimedia 9(2):52–60

    Article  Google Scholar 

  3. Babaguchi N, Kawai Y, Ogura T, Kitahashi T (2004) Personalized abstraction of broadcasted american football video by highlight selection. IEEE Trans Multimedia 6(4):107–109

    Article  Google Scholar 

  4. Baillie M, Jose JM (2003) Audio-based event detection for sports video. In: Lecture notes on computer science, vol 2728, pp 61–66

  5. Bao P, Zhang L, Wu X (2005) Canny edge detection enhancement by scale multiplication. In: IEEE trans. on pattern recognition and machine intelligence, vol 27, pp 1485–1490

  6. Baoxin L, Pan H, Sezan I (2003) A general framework for sports video summarization with its application to soccer. In: Proc. of int conf on acoustics, speech and signal processing, vol 3, no 169–172

  7. Bertini M, Cucchiara R, Bimbo AD, Prati A (2005) An integrated framework for semantic annotation and adaptation. Int J Multimed Tools Appl 26:345–363

    Article  Google Scholar 

  8. Cheng C, Hsu C (2006) Fusion of audio and motion information on HMM-based highlight extraction for baseball games. IEEE Trans Multimedia 8(3):585–599

    Article  Google Scholar 

  9. Chang P, Han M, Gong Y (2002) Extract highlights from baseball game video with hidden markov models. Proc Int Conf Image Proc 1:609–612

    Google Scholar 

  10. Christel M, Stevens S, Kanade T, Mauldin M, Reddy R, Wactlar H (1995) Techniques for the creation and exploration of digital video libraries. Multimed Tools Appl 2

  11. Dimitrova N, Zhang HJ, Shahraray B, Sezan I, Huang T, Zakhor A (2002) Applications of video-content analysis and retrieval. IEEE Multimedia 9(3):42–55

    Article  Google Scholar 

  12. Duan L, Xu M, Tian Q, Xu C, Jin J (2005) A unified framework for semantic shot classification in sports video. IEEE Trans Multimedia 7(6):1066–1083

    Article  Google Scholar 

  13. Ekin A, Tekalp AM, Mehrotra R (2003) Automatic soccer video analysis and summarization. IEEE Trans Image Process 12(7):796–807

    Article  Google Scholar 

  14. Gauch JM, Shivadas A (2005) Identification of new commercials using repeated video sequence detection. IEEE Int Conf Image Proc 3:1252–1255

    Google Scholar 

  15. Hanjalic A (2005) Adaptive extraction of highlights from a sport video based on excitement modeling. IEEE Trans Multimedia 7(6):1114–1122

    Article  Google Scholar 

  16. Hua W, Han M, Gong Y (2002) Baseball scene classification using multimedia features. In: Proc of IEEE int. conf. on multimedia and expo, vol 1, pp 821–824

  17. Hua XS, Lu L, Zhang HJ (2005) Robust learning-based TV commercial detection. In: IEEE int. conf. multimedia and expo, pp 149–152

  18. Huang J, Liu Z, Wang Y (2005) Joint scene classification and segmentation based on hidden markov model. IEEE Trans Multimedia 7(3):538–550

    Article  Google Scholar 

  19. Hauptmann AG, Smith M (1995) Text, speech and vision for video segmentation: the informedia project. writing notes of ijcai workshop on intelligent multimedia information retrieval, pp 17–22

  20. Kijak E, Gravier G, Gros P, Oisel L, Bimbot F (2003) HMM based structuring of tennis videos using visual and audio cue. In: Proc. of int. conf. on multimedia and expo, vol 3, pp 309–312

  21. Kokaram A, Rea N, Dahyot R, Tekalp M, Bouthemy P, Gros P, Sezan I (2006) Browsing sports video: trends in sports-related indexing and retrieval work. IEEE Signal Process Mag 23(2):47–58

    Article  Google Scholar 

  22. Kolekar MH, Sengupta S (2004) Hidden markov model based video indexing with discrete cosine transform as a likelihood function. In: IEEE INDICON conference, IIT Kharagpur, India, pp 157–159

  23. Kolekar MH, Sengupta S (2005) Semantic indexing of news video sequences: a multimodal hierarchical approach based on hidden markov model. In: Proc of IEEE int. region 10 conference (TENCON), Melbourne, pp 1–5

  24. Kolekar MH, Sengupta S (2006) A hierarchical framework for generic sports video classification. In: Lecture notes on computer science, vol 3852. Springer, Berlin, pp 633–642

    Google Scholar 

  25. Kolekar MH, Sengupta S (2006) Event-importance based customized and automatic cricket highlight generation. In: IEEE int. conf. on multimedia and expo, pp 1617–1620

  26. Kolekar MH, Sengupta S (2006) Semantic concept extraction from sports video for highlight generation. In: Proc. of ACM int. conf. on mobile multimedia communication, vol 324

  27. Kolekar MH, Talbar SN, Sontakke TR (2000) Texture segmentation using fractal signature. IETE J Research 46(5):319–323

    Google Scholar 

  28. Leonardi R, Migliorati P, Prandini M (2004) Semantic indexing of soccer audio-visual sequences: a multimodal approach based on controlled markov chains. IEEE Trans Circuits Syst Video Technol 14(5)

  29. Li B, Sezan MI (2003) Semantic sports video analysis: approaches and new applications. Proc IEEE Int Conf Image Proc 1:17–20

    Google Scholar 

  30. Mei T, Ma YF, Zhou HQ, Ma WY, Zhang HJ (2005) Sports video mining with mosaic. In: IEEE—Multimedia Modeling Conference, pp 107–114

  31. Naphade MR, Smith JR (2004) On the detection of semantic concepts at trecvid. In: 12th annual ACM int. conf. on multimedia, pp 660–667

  32. Otsuka I, Nakane K, Divakaran A, Hatanaka K, Ogawa M (2005) A highlight scene detection and video summarization system using audio feature for a personal video recorder. IEEE Trans Consum Electron 51(1):112–116

    Article  Google Scholar 

  33. Peker K, Cabasson R, Divakaran A (2002) Rapid generation of sports video highlights using the mpeg-7 motion activity descriptor. In: Proc SPIE storage and retrieval for media databases, vol 4676, pp 318–323

  34. Rui Y, Gupta A, Acero A (2000) Automatically extracting highlights for tv baseball programs. In: Proc. ACM multimedia, pp 105–115

  35. Sankar KP, Pandey S, Jawahar CV (2006) Text driven temporal segmentation of cricket videos. Int Conf Pattern Recognit 4338:433–444

    Google Scholar 

  36. Takahashi Y, Nitta N, Babaguchi N (2005) Video summarization for large sports video archives. In: Proc IEEE int. conf. multimedia and expo, pp 1170–1173

  37. Utsumi O, Miura K, Ide I, Sakai S, Tanaka H (2002) An object detection method for describing soccer games from video. In: Proc of IEEE int. conf. on multimedia and expo, vol 1, pp 45–48

  38. Wan K, Xu C (2004) Efficient multimodal features for automatic soccer highlight generation. Int Conf Pattern Recognit 3:973–976

    Google Scholar 

  39. Wang J, Chng E, Xu C, Hanqinq L, Tian Q (2007) Generation of personalized music sports video using multimodal cues. IEEE Trans Multimedia 9(3):576–588

    Article  Google Scholar 

  40. Xiong Z, Radhakrishnan R, Divakaran A, Huang TS (2003) Audio events detection based highlights extraction from baseball, golf, soccer games in a unified framework. In: Proc. int. conf. on acoustics, speech and signal processing, vol 5, pp 632–635

  41. Xu H, Chau T (2004) The fusion of audio-visual features and external knowledge for event detection in team sports video. In: ACM SIGMM int. multimedia workshop on multimedia information retrieval, pp 127–134

  42. Xu P, Xie L, Chang S, Divakaran A, Vetro A, Sun H (2001) Algorithms and system for segmentation and structure analysis in soccer video. In: IEEE int. conf. on multimedia and expo

  43. Zhang Z, Masseglia F, Jain R, Bimbo AD (2008) Editorial: introduction to the special issue on multimedia data mining. IEEE Trans Multimedia 10(2):165–166

    Article  Google Scholar 

  44. Zhou W, Vellaikal A, Kuo CCJ (2000) Rule-based video classification system for basketball video indexing. In: Proc. ACM workshop on multimedia, pp 213–216

  45. Zhu X, Wu X, Elmagarmid AK, Feng Z, Wu L (2005) Video data mining: semantic indexing and event detection from the association perspective. IEEE Trans Knowl Data Eng 17(5):665–677

    Article  Google Scholar 

  46. Zhu G, Huang Q, Xu C, Xing L, Gao W, Yao H (2007) Human behavior analysis for highlight ranking in broadcast racket sports video. IEEE Trans Multimedia 9(6):1167–1182

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Missouri, Columbia, MO, USA

    Maheshkumar H. Kolekar

  2. Electronics and Electrical Communication Engg, Indian Institute of Technology, Kharagpur, India

    Somnath Sengupta

Authors
  1. Maheshkumar H. Kolekar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Somnath Sengupta
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Maheshkumar H. Kolekar.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kolekar, M.H., Sengupta, S. Semantic concept mining in cricket videos for automated highlight generation. Multimed Tools Appl 47, 545–579 (2010). https://doi.org/10.1007/s11042-009-0337-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-009-0337-1

Keywords

Search

Navigation