Abstract
The analytics of lifelogging has generated great interest for data scientists because big and multi-dimensional data are generated as a result of lifelogging activities. In this paper, the NTCIR Lifelog dataset is used to learn activities from an image point of view. Minute definitions are classified into activity classes using images and annotations, which serve as a basis for various classification techniques, namely SVMs and convolutional neural network structures (CNN), for learning activities. The performance of the classification methods used in this study is evaluated and compared.
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References
Amlinger, A.: An evaluation of clustering and classification algorithms in life-logging devices. Ph.D. thesis (2015). http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121630
Belimpasakis, P., Roimela, K., You, Y.: Experience explorer: a life-logging platform based on mobile context collection. In: 2009 Third International Conference on Next Generation Mobile Applications, Services and Technologies (2009). https://doi.org/10.1109/ngmast.2009.49
Bolaños, M., Dimiccoli, M., Radeva, P.: Towards storytelling from visual lifelogging: an overview. CoRR abs/1507.06120 (2015). http://arxiv.org/abs/1507.06120
Dimiccoli, M., Cartas, A., Radeva, P.: Activity recognition from visual lifelogs: state of the art and future challenges. In: Multimodal Behavior Analysis in the Wild, pp. 121–134 (2019). https://doi.org/10.1016/b978-0-12-814601-9.00017-1
Gurrin, C., Joho, H., Hopfgartner, F., Zhou, L., Albatal, R.: Overview of NTCIR-12 lifelog task. In: Kando, N., Kishida, K., Kato, M.P., Yamamoto, S. (eds.) Proceedings of the 12th NTCIR Conference on Evaluation of Information Access Technologies, pp. 354–360 (2016). http://eprints.gla.ac.uk/131460/
Gurrin, C., et al.: Overview of NTCIR-13 lifelog-2 task. In: Proceedings of the 13th NTCIR Conference on Evaluation of Information Access Technologies (2017). http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings13/pdf/ntcir/01-NTCIR13-OV-LIFELOG-GurrinC.pdf
He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. CoRR abs/1512.03385 (2015). http://arxiv.org/abs/1512.03385
Lin, H.L., Chiang, T.C., Chen, L.P., Yang, P.C.: Image searching by events with deep learning for NTCIR-12 lifelog. In: Proceedings of the 12th NTCIR Conference on Evaluation of Information Access Technologies (2016)
Lin, J., Lim, J.H.: VCI2R at the NTCIR-13 lifelog-2 lifelog semantic access task (2017)
Mann, S.: Wearable computing: a first step toward personal imaging. Computer 30(2), 25–32 (1997). https://doi.org/10.1109/2.566147
del Molino, A.G., Mandal, B., Lin, J., Lim, J.H., Subbaraju, V., Chandrasekhar, V.: VC-I2R@ImageCLEF2017: ensemble of deep learned features for lifelog video summarization. In: CLEF (2017)
Safadi, B., Mulhem, P., Quénot, G., Chevallet, J.P.: LIG-MRIM at NTCIR-12 lifelog semantic access task. In: NTCIR (2016)
Truong, T.D., Dinh-Duy, T., Nguyen, V.T., Tran, M.T.: Lifelogging retrieval based on semantic concepts fusion. In: Proceedings of the 2018 ACM Workshop on the Lifelog Search Challenge - LSC 2018 (2018). https://doi.org/10.1145/3210539.3210545
Xia, L., Ma, Y., Fan, W.: VTIR at the NTCIR-12 2016 lifelog semantic access task. In: NTCIR (2016)
Yamamoto, S., Nishimura, T., Takimoto, Y., Inoue, T., Toda, H.: PBG at the NTCIR-13 lifelog-2 LAT, LSAT, and LEST tasks (2017)
Acknowledgement
This study is supported in part by NU Faculty - development competitive research grants program, Nazarbayev University, Grant Number - 110119FD4543.
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Belli, K., Akbaş, E., Yazici, A. (2019). Activity Learning from Lifelogging Images. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11509. Springer, Cham. https://doi.org/10.1007/978-3-030-20915-5_30
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DOI: https://doi.org/10.1007/978-3-030-20915-5_30
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