Skip to main content

LifeCLEF 2014: Multimedia Life Species Identification Challenges

  • Conference paper
Information Access Evaluation. Multilinguality, Multimodality, and Interaction (CLEF 2014)

Abstract

Using multimedia identification tools is considered as one of the most promising solutions to help bridging the taxonomic gap and build accurate knowledge of the identity, the geographic distribution and the evolution of living species. Large and structured communities of nature observers (e.g. eBird, Xeno-canto, Tela Botanica, etc.) as well as big monitoring equipments have actually started to produce outstanding collections of multimedia records. Unfortunately, the performance of the state-of-the-art analysis techniques on such data is still not well understood and is far from reaching the real world’s requirements. The LifeCLEF lab proposes to evaluate these challenges around three tasks related to multimedia information retrieval and fine-grained classification problems in three living worlds. Each task is based on large and real-world data and the measured challenges are defined in collaboration with biologists and environmental stakeholders in order to reflect realistic usage scenarios. This paper presents more particularly the 2014 edition of LifeCLEF, i.e. the pilot one. For each of the three tasks, we report the methodology and the datasets as well as the official results and the main outcomes.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. MAED 2012: Proceedings of the 1st ACM International Workshop on Multimedia Analysis for Ecological Data. ACM, New York (2012) 433127

    Google Scholar 

  2. Inria’s participation at ImageCLEF 2013 Plant Identification Task. In: CLEF (Online Working Notes/Labs/Workshop) 2013, Valencia, Espagne (2013)

    Google Scholar 

  3. Proc. of the first workshop on Machine Learning for Bioacoustics (2013)

    Google Scholar 

  4. Angelova, A., Zhu, S., Lin, Y., Wong, J., Shpecht, C.: Development and deployment of a large-scale flower recognition mobile app. Technical report (December 2012)

    Google Scholar 

  5. Aptoula, E., Yanikoglu, B.: Morphological features for leaf based plant recognition. In: Proc. IEEE Int. Conf. Image Process., Melbourne, Australia, p. 7 (2013)

    Google Scholar 

  6. Backes, A.R., Casanova, D., Bruno, O.M.: Plant leaf identification based on volumetric fractal dimension. International Journal of Pattern Recognition and Artificial Intelligence 23(6), 1145–1160 (2009)

    Article  Google Scholar 

  7. Baillie, J., Hilton-Taylor, C., Stuart, S.: 2004 iucn red list of threatened species. a global species assessment. IUCN, Gland, Switzerland and Cambridge, UK (2004)

    Google Scholar 

  8. Barnich, O., Van Droogenbroeck, M.: Vibe: A universal background subtraction algorithm for video sequences. IEEE Transactions on Image Processing 20(6), 1709–1724 (2011)

    Article  MathSciNet  Google Scholar 

  9. Blanc, K., Lingrand, D., Precioso, F.: Fish species recognition from video using svm classifier. In: Working Notes of CLEF 2014 Conference (2014)

    Google Scholar 

  10. Briggs, F., Lakshminarayanan, B., Neal, L., Fern, X.Z., Raich, R., Hadley, S.J., Hadley, A.S., Betts, M.G.: Acoustic classification of multiple simultaneous bird species: A multi-instance multi-label approach. The Journal of the Acoustical Society of America 131, 4640 (2012)

    Article  Google Scholar 

  11. Cai, J., Ee, D., Pham, B., Roe, P., Zhang, J.: Sensor network for the monitoring of ecosystem: Bird species recognition. In: 3rd International Conference on Intelligent Sensors, Sensor Networks and Information, ISSNIP 2007, pp. 293–298 (December 2007)

    Google Scholar 

  12. Cerutti, G., Tougne, L., Vacavant, A., Coquin, D.: A parametric active polygon for leaf segmentation and shape estimation. In: Bebis, G. (ed.) ISVC 2011, Part I. LNCS, vol. 6938, pp. 202–213. Springer, Heidelberg (2011)

    Google Scholar 

  13. Chen, Q., Abedini, M., Garnavi, R., Liang, X.: Ibm research australia at lifeclef2014: Plant identification task. In: Working notes of CLEF 2014 Conference (2014)

    Google Scholar 

  14. Concetto, S., Fisher, B., Boom, B.: Lifeclef fish identification task 2014. In: CLEF Working Notes (2014)

    Google Scholar 

  15. Dimitrovski, I., Madjarov, G., Lameski, P., Kocev, D.: Maestra at lifeclef 2014 plant task: Plant identification using visual data. In: Working Notes of CLEF 2014 Conference (2014)

    Google Scholar 

  16. Dufour, O., Artieres, T., Glotin, H., Giraudet, P.: Clusterized mel filter cepstral coefficients and support vector machines for bird song idenfication (2013)

    Google Scholar 

  17. Eyben, F., Wöllmer, M., Schuller, B.: Opensmile: the munich versatile and fast open-source audio feature extractor. In: Proceedings of the International Conference on Multimedia, pp. 1459–1462. ACM (2010)

    Google Scholar 

  18. Fakhfakh, S., Akrout, B., Tmar, M., Mahdi, W.: A visual search of multimedia documents in lifeclef 2014. In: Working Notes of CLEF 2014 Conference (2014)

    Google Scholar 

  19. Gaston, K.J., O’Neill, M.A.: Automated species identification: why not? 359(1444), 655–667 (2004)

    Google Scholar 

  20. Glotin, H., Sueur, J.: Overview of the first international challenge on bird classification (2013)

    Google Scholar 

  21. Goëau, H., Bonnet, P., Joly, A., Bakić, V., Barbe, J., Yahiaoui, I., Selmi, S., Carré, J., Barthélémy, D., Boujemaa, N.: et al. Pl@ ntnet mobile app. In: Proceedings of the 21st ACM International Conference on Multimedia, pp. 423–424. ACM (2013)

    Google Scholar 

  22. Goëau, H., Bonnet, P., Joly, A., Boujemaa, N., Barthélémy, D., Molino, J.-F., Birnbaum, P., Mouysset, E., Picard, M.: The ImageCLEF 2011 plant images classification task. In: CLEF Working Notes (2011)

    Google Scholar 

  23. Goëau, H., Bonnet, P., Joly, A., Yahiaoui, I., Barthelemy, D., Boujemaa, N., Molino, J.-F.: The imageclef 2012 plant identification task. In: CLEF Working Notes (2012)

    Google Scholar 

  24. Goëau, H., Glotin, H., Vellinga, W.-P., Rauber, A.: Lifeclef bird identification task (2014)

    Google Scholar 

  25. Goëau, H., Joly, A., Bonnet, P., Molino, J.-F., Barthélémy, D., Boujemaa, N.: Lifeclef plant identification task 2014. In: CLEF Working Notes 2014 (2014)

    Google Scholar 

  26. Goëau, H., Joly, A., Selmi, S., Bonnet, P., Mouysset, E., Joyeux, L., Molino, J.-F., Birnbaum, P., Bathelemy, D., Boujemaa, N.: Visual-based plant species identification from crowdsourced data. In: ACM Conference on Multimedia, pp. 813–814 (2011)

    Google Scholar 

  27. Goëau, H., Joly, A., Yahiaoui, I., Bakić, V., Anne, V.-B.: Pl@ntnet’s participation at lifeclef 2014 plant identification task. In: Working notes of CLEF 2014 Conference (2014)

    Google Scholar 

  28. Hazra, A., Deb, K., Kundu, S., Hazra, P., et al.: Shape oriented feature selection for tomato plant identification. International Journal of Computer Applications Technology and Research 2(4), 449–meta (2013)

    Google Scholar 

  29. Issolah, M., Lingrand, D., Precioso, F.: Plant species recognition using bag-of-word with svm classifier in the context of the lifeclef challenge. In: Working notes of CLEF 2014 Conference (2014)

    Google Scholar 

  30. Joalland, P.-H., Paris, S., Glotin, H.: Efficient instance-based fish species visual identification by global representation. In: Working Notes of CLEF 2014 Conference (2014)

    Google Scholar 

  31. Joly, A., Champ, J., Buisson, O.: Instance-based bird species identification with undiscriminant features pruning - lifeclef2014. In: Working Notes of CLEF 2014 Conference (2014)

    Google Scholar 

  32. Joly, A., Goeau, H., Bonnet, P., Bakić, V., Barbe, J., Selmi, S., Yahiaoui, I., Carré, J., Mouysset, E., Molino, J.-F., Boujemaa, N., Barthélémy, D.: Interactive plant identification based on social image data. Ecological Informatics (2013)

    Google Scholar 

  33. Joly, A., Goëau, H., Bonnet, P., Bakic, V., Molino, J.-F., Barthélémy, D., Boujemaa, N.: The Imageclef Plant Identification Task 2013. In: International Workshop on Multimedia Analysis for Ecological Data, Barcelone, Espagne (October 2013)

    Google Scholar 

  34. Karamti, H., Fakhfakh, S., Tmar, M., Gargouri, F.: Miracl at lifeclef 2014: Multi-organ observation for plant identification. In: Working notes of CLEF 2014 Conference (2014)

    Google Scholar 

  35. Kavasidis, I., Palazzo, S., Salvo, R., Giordano, D., Spampinato, C.: An innovative web-based collaborative platform for video annotation. In: Multimedia Tools and Applications, pp. 1–20 (2013)

    Google Scholar 

  36. Kebapci, H., Yanikoglu, B., Unal, G.: Plant image retrieval using color, shape and texture features. The Computer Journal 54(9), 1475–1490 (2011)

    Article  Google Scholar 

  37. Kumar, N., Belhumeur, P.N., Biswas, A., Jacobs, D.W., Kress, W.J., Lopez, I.C., Soares, J.V.B.: Leafsnap: A computer vision system for automatic plant species identification. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012, Part II. LNCS, vol. 7573, pp. 502–516. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  38. Lasseck, M.: Large-scale identification of birds in audio recordings. In: Working notes of CLEF 2014 Conference (2014)

    Google Scholar 

  39. Lee, D.-J., Schoenberger, R.B., Shiozawa, D., Xu, X., Zhan, P.: Contour matching for a fish recognition and migration-monitoring system. In: Optics East, pp. 37–48. International Society for Optics and Photonics (2004)

    Google Scholar 

  40. Martinez, R., Silvan, L., Villarreal, E.V., Fuentes, G., Meza, I.: Svm candidates and sparse representation for bird identification. In: Working notes of CLEF 2014 Conference (2014)

    Google Scholar 

  41. Mouine, S., Yahiaoui, I., Verroust-Blondet, A.: Advanced shape context for plant species identification using leaf image retrieval. In: ACM International Conference on Multimedia Retrieval, pp. 49:1–49:8 (2012)

    Google Scholar 

  42. Nilsback, M.-E., Zisserman, A.: Automated flower classification over a large number of classes. In: Indian Conference on Computer Vision, Graphics and Image Processing, pp. 722–729 (2008)

    Google Scholar 

  43. Northcott, J.: Overview of the lifeclef 2014 bird task. In: Working Notes of CLEF 2014 Conference (2014)

    Google Scholar 

  44. Paczolay, D., Bánhalmi, A., Nyúl, L., Bilicki, V., Sárosi, Á.: Wlab of university of szeged at lifeclef 2014 plant identification task. In: Working notes of CLEF 2014 Conference (2014)

    Google Scholar 

  45. Paris, S., Halkias, X., Glotin, H.: Sparse coding for histograms of local binary patterns applied for image categorization: toward a bag-of-scenes analysis. In: 2012 21st International Conference on Pattern Recognition (ICPR), pp. 2817–2820. IEEE (2012)

    Google Scholar 

  46. Ren, L.Y., William Dennis, J., Huy Dat, T.: Bird classification using ensemble classifiers. In: Working notes of CLEF 2014 Conference (2014)

    Google Scholar 

  47. Shortis, M.R., Ravanbakskh, M., Shaifat, F., Harvey, E.S., Mian, A., Seager, J.W., Culverhouse, P.F., Cline, D.E., Edgington, D.R.: A review of techniques for the identification and measurement of fish in underwater stereo-video image sequences. In: SPIE Optical Metrology 2013, pp. 87910G–87910G. International Society for Optics and Photonics (2013)

    Google Scholar 

  48. Spampinato, C., Beauxis-Aussalet, E., Palazzo, S., Beyan, C., Ossenbruggen, J., He, J., Boom, B., Huang, X.: A rule-based event detection system for real-life underwater domain. Machine Vision and Applications 25(1), 99–117 (2014)

    Article  Google Scholar 

  49. Spampinato, C., Chen-Burger, Y.-H., Nadarajan, G., Fisher, R.B.: Detecting, tracking and counting fish in low quality unconstrained underwater videos. In: VISAPP (2), pp. 514–519. Citeseer (2008)

    Google Scholar 

  50. Spampinato, C., Giordano, D., Di Salvo, R., Chen-Burger, Y.-H.J., Fisher, R.B., Nadarajan, G.: Automatic fish classification for underwater species behavior understanding. In: Proceedings of ACM ARTEMIS 2010, pp. 45–50. ACM (2010)

    Google Scholar 

  51. Stowell, D., Plumbley, M.D.: Audio-only bird classification using unsupervised feature learning. In: Working notes of CLEF 2014 Conference (2014)

    Google Scholar 

  52. Sunderhauf, N., McCool, C., Upcroft, B., Tristan, P.: Fine-grained plant classification using convolutional neural networks for feature extraction. In: Working Notes of CLEF 2014 Conference (2014)

    Google Scholar 

  53. Szúcs, G., Dávid, P., Lovas, D.: Viewpoints combined classification method in image-based plant identification task. In: Working Notes of CLEF 2014 Conference (2014)

    Google Scholar 

  54. Towsey, M., Planitz, B., Nantes, A., Wimmer, J., Roe, P.: A toolbox for animal call recognition. Bioacoustics 21(2), 107–125 (2012)

    Article  Google Scholar 

  55. Trifa, V.M., Kirschel, A.N., Taylor, C.E., Vallejo, E.E.: Automated species recognition of antbirds in a mexican rainforest using hidden markov models. The Journal of the Acoustical Society of America 123, 2424 (2008)

    Article  Google Scholar 

  56. Vedaldi, A., Fulkerson, B.: Vlfeat: An open and portable library of computer vision algorithms. In: Proceedings of the International Conference on Multimedia, pp. 1469–1472. ACM (2010)

    Google Scholar 

  57. Vincent Koops, H., van Balen, J., Wiering, F.: A deep neural network approach to the lifeclef 2014 bird task. In: Working notes of CLEF 2014 Conference (2014)

    Google Scholar 

  58. Wheeler, Q.D., Raven, P.H., Wilson, E.O.: Taxonomy: Impediment or expedient? Science, 303(5656), 285 (2004)

    Google Scholar 

  59. Yanikoglu, B., Tolga, Y.S., Tirkaz, C., FuenCaglartes, E.: Sabanci-okan system at lifeclef 2014 plant identification competition. In: Working notes of CLEF 2014 Conference (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Joly, A. et al. (2014). LifeCLEF 2014: Multimedia Life Species Identification Challenges. In: Kanoulas, E., et al. Information Access Evaluation. Multilinguality, Multimodality, and Interaction. CLEF 2014. Lecture Notes in Computer Science, vol 8685. Springer, Cham. https://doi.org/10.1007/978-3-319-11382-1_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-11382-1_20

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11381-4

  • Online ISBN: 978-3-319-11382-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics