A Betancourt, P Morerio, CS Regazzoni, M Rauterberg, The evolution of first person vision methods: a survey. IEEE Trans. Circ. Syst. Video Technol.25(5), 744–760 (2015).
Z Lu, K Grauman, in Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference On. Story-driven summarization for egocentric video, (2013), pp. 2714–2721.
MS Ryoo, L Matthies, in Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference On. First-person activity recognition: what are they doing to me?, (2013), pp. 2730–2737.
A Krizhevsky, I Sutskever, GE Hinton, in Advances in Neural Information Processing Systems 25, ed. by F Pereira, CJC Burges, L Bottou, and KQ Weinberger. Imagenet classification with deep convolutional neural networks, (2012), pp. 1097–1105.
A Takamine, Y Iwashita, R Kurazume, in 2015 IEEE/SICE International Symposium on System Integration (SII). First-person activity recognition with c3d features from optical flow images, (2015), pp. 619–622.
M Ma, H Fan, KM Kitani, in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Going deeper into first-person activity recognition, (2016), pp. 1894–1903.
S Song, V Chandrasekhar, B Mandal, L Li, J-H Lim, G Sateesh Babu, P Phyo San, N-M Cheung, in The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. Multimodal multi-stream deep learning for egocentric activity recognition, (2016), pp. 378–385.
D Crandall, C Fan, in European Conference on Computer Vision International Workshop on Egocentric Perception, Interaction, and Computing (EPIC). Deepdiary: automatically captioning lifelogging image streams (Springer International PublishingCham, 2016), pp. 459–473.
O Russakovsky, J Deng, H Su, J Krause, S Satheesh, S Ma, Z Huang, A Karpathy, A Khosla, M Bernstein, AC Berg, L Fei-Fei, ImageNet large scale visual recognition challenge. Int. J. Comput. Vision (IJCV). 115(3), 211–252 (2015).
B Zhou, A Khosla, À Lapedriza, A Torralba, A Oliva, Places: an image database for deep scene understanding. CoRR.abs/1610.02055: (2016).
D Castro, S Hickson, V Bettadapura, E Thomaz, G Abowd, H Christensen, I Essa, in Proceedings of the 2015 ACM International Symposium on Wearable Computers. ISWC ’15. Predicting daily activities from egocentric images using deep learning, (2015), pp. 75–82.
A Bulling, JA Ward, H Gellersen, G Tröster, Robust recognition of reading activity in transit using wearable electrooculography. (J Indulska, DJ Patterson, T Rodden, M Ott, eds.) (Springer, Berlin, Heidelberg, 2008).
T Kimura, R Huang, S Uchida, M Iwamura, S Omachi, K Kise, in 2013 12th International Conference on Document Analysis and Recognition. The reading-life log—technologies to recognize texts that we read, (2013), pp. 91–95.
K Kunze, Y Shiga, S Ishimaru, K Kise, in 2013 12th International Conference on Document Analysis and Recognition. Reading activity recognition using an off-the-shelf EEG—detecting reading activities and distinguishing genres of documents, (2013), pp. 96–100.
K Kise, O Augereau, Y Utsumi, M Iwamura, K Kunze, S Ishimaru, A Dengel, in Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers. UbiComp ’17. Quantified reading and learning for sharing experiences, (2017), pp. 724–731.
AM Khan, YK Lee, SY Lee, TS Kim, A triaxial accelerometer-based physical-activity recognition via augmented-signal features and a hierarchical recognizer. IEEE Trans. Inf. Technol. Biomed.14(5), 1166–1172 (2010).
M Zhang, AA Sawchuk, Human daily activity recognition with sparse representation using wearable sensors. IEEE J. Biomed. Health Inf.17(3), 553–560 (2013).
C Yan, Y Zhang, F Dai, J Zhang, L Li, Q Dai, Efficient parallel hevc intra-prediction on many-core processor. Electron. Lett.50(11), 805–806 (2014).
C Yan, Y Zhang, F Dai, X Wang, L Li, Q Dai, Parallel deblocking filter for hevc on many-core processor. Electron. Lett.50(5), 367–368 (2014).
C Yan, Y Zhang, J Xu, F Dai, J Zhang, Q Dai, F Wu, Efficient parallel framework for HEVC motion estimation on many-core processors. IEEE Trans. Circ. Syst. Video Technol.24(12), 2077–2089 (2014).
C Yan, Y Zhang, J Xu, F Dai, L Li, Q Dai, F Wu, A highly parallel framework for HEVC coding unit partitioning tree decision on many-core processors. IEEE Signal Proc. Lett.21(5), 573–576 (2014).
EH Spriggs, FDL Torre, M Hebert, in 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. Temporal segmentation and activity classification from first-person sensing, (2009), pp. 17–24.
KM Kitani, T Okabe, Y Sato, A Sugimoto, in Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference On. Fast unsupervised ego-action learning for first-person sports videos, (2011), pp. 3241–3248.
A Fathi, A Farhadi, JM Rehg, in Proceedings of the 2011 International Conference on Computer Vision. ICCV ’11. Understanding egocentric activities, (2011), pp. 407–414.
H Pirsiavash, D Ramanan, in Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference On. Detecting activities of daily living in first-person camera views, (2012), pp. 2847–2854.
K Zhan, F Ramos, S Faux, in Control Automation Robotics Vision (ICARCV), 2012 12th International Conference On. Activity recognition from a wearable camera, (2012), pp. 365–370.
K Zhan, V Guizilini, F Ramos, in Control Automation Robotics Vision (ICARCV), 2014 13th International Conference On. Dense motion segmentation for first-person activity recognition, (2014), pp. 123–128.
Y Yan, E Ricci, G Liu, N Sebe, Egocentric daily activity recognition via multitask clustering. IEEE Trans. Image Process.24(10), 2984–2995 (2015).
L Xia, I Gori, JK Aggarwal, MS Ryoo, in 2015 IEEE Winter Conference on Applications of Computer Vision. Robot-centric activity recognition from first-person RGB-D videos, (2015), pp. 357–364.
K Simonyan, A Zisserman, Very deep convolutional networks for large-scale image recognition. CoRR.abs/1409.1556: (2014).
C Szegedy, W Liu, Y Jia, P Sermanet, SE Reed, D Anguelov, D Erhan, V Vanhoucke, A Rabinovich, Going deeper with convolutions. CoRR.abs/1409.4842: (2014).
K He, X Zhang, S Ren, J Sun, in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Deep residual learning for image recognition, (2016), pp. 770–778.
MS Ryoo, B Rothrock, L Matthies, in 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Pooled motion features for first-person videos, (2015), pp. 896–904.
SC Wong, A Gatt, V Stamatescu, MD McDonnell, Understanding data augmentation for classification: when to warp?. CoRR.abs/1609.08764: (2016).
O Khalil, ME Fathy, DKE Kholy, ME Saban, P Kohli, J Shotton, Y Badr, in 2013 IEEE International Conference on Image Processing. Synthetic training in object detection, (2013), pp. 3113–3117.
A Gupta, A Vedaldi, A Zisserman, in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Synthetic data for text localisation in natural images, (2016), pp. 2315–2324.
B Sun, K Saenko, in Proceedings of the British Machine Vision Conference. From virtual to reality: fast adaptation of virtual object detectors to real domains, (2014).
H Su, CR Qi, Y Li, LJ Guibas, in 2015 IEEE International Conference on Computer Vision (ICCV). Render for CNN: viewpoint estimation in images using CNNC trained with rendered 3d model views, (2015), pp. 2686–2694.
E Castro, A Ulloa, SM Plis, JA Turner, VD Calhoun, in 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI). Generation of synthetic structural magnetic resonance images for deep learning pre-training, (2015), pp. 1057–1060.
C Szegedy, V Vanhoucke, S Ioffe, J Shlens, Z Wojna, Rethinking the inception architecture for computer vision. CoRR.abs/1512.00567: (2015).
S Song, V Chandrasekhar, N-M Cheung, S Narayan, L Li, J-H Lim, in ACCV Workshops (3). Activity recognition in egocentric life-logging videos (Springer International PublishingCham, 2014), pp. 445–458.
S Song, NM Cheung, V Chandrasekhar, B Mandal, J Liri, in 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Egocentric activity recognition with multimodal Fisher vector, (2016), pp. 2717–2721.
F Perronnin, J Sánchez, T Mensink, in Proceedings of the 11th European Conference on Computer Vision: Part IV. ECCV’10. Improving the Fisher kernel for large-scale image classification (SpringerBerlin, 2010), pp. 143–156.
G Csurka, CR Dance, L Fan, J Willamowski, C Bray, in In Workshop on Statistical Learning in Computer Vision, ECCV. Visual categorization with bags of keypoints, (2004), pp. 1–22.