메뉴 건너뛰기




Volumn 2016-December, Issue , 2016, Pages 1229-1238

Recurrent attention models for depth-based person identification

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; PATTERN RECOGNITION; REINFORCEMENT LEARNING; THREE DIMENSIONAL COMPUTER GRAPHICS;

EID: 84986309164     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2016.138     Document Type: Conference Paper
Times cited : (175)

References (81)
  • 1
    • 84959241040 scopus 로고    scopus 로고
    • An improved deep learning architecture for person re-identification
    • E. Ahmed, M. Jones, and T. K. Marks. An improved deep learning architecture for person re-identification. In CVPR, 2015.
    • (2015) CVPR
    • Ahmed, E.1    Jones, M.2    Marks, T.K.3
  • 2
    • 84911443405 scopus 로고    scopus 로고
    • Socially-aware large-scale crowd forecasting
    • A. Alahi, V. Ramanathan, and L. Fei-Fei. Socially-aware large-scale crowd forecasting. In CVPR, 2014.
    • (2014) CVPR
    • Alahi, A.1    Ramanathan, V.2    Fei-Fei, L.3
  • 3
    • 85009918233 scopus 로고    scopus 로고
    • Who is who at different cameras: People re-identification using depth cameras
    • A. Albiol, J. Oliver, and J. M. Mossi. Who is who at different cameras: people re-identification using depth cameras. Computer Vision, 2012.
    • (2012) Computer Vision
    • Albiol, A.1    Oliver, J.2    Mossi, J.M.3
  • 4
    • 84905641597 scopus 로고    scopus 로고
    • Anthropometric and human gait identification using skeleton data from kinect sensor
    • V. Andersson, R. Dutra, and R. Araújo. Anthropometric and human gait identification using skeleton data from kinect sensor. In Symposium on Applied Computing. ACM, 2014.
    • (2014) Symposium on Applied Computing. ACM
    • Andersson, V.1    Dutra, R.2    Araújo, R.3
  • 9
    • 77956502203 scopus 로고    scopus 로고
    • A theoretical analysis of feature pooling in visual recognition
    • Y.-L. Boureau, J. Ponce, and Y. LeCun. A theoretical analysis of feature pooling in visual recognition. In ICML, 2010.
    • (2010) ICML
    • Boureau, Y.-L.1    Ponce, J.2    LeCun, Y.3
  • 10
    • 84956626439 scopus 로고    scopus 로고
    • Utd-mhad: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor
    • R. J. C. Chen and N. Kehtarnavaz. Utd-mhad: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor. In ICIP, 2015.
    • (2015) ICIP
    • Chen, R.J.C.1    Kehtarnavaz, N.2
  • 11
    • 84986262991 scopus 로고    scopus 로고
    • Semantic guidance of visual attention for localizing objects in scenes
    • J. Caicedo and S. Lazebnik. Semantic guidance of visual attention for localizing objects in scenes. ICCV, 2015.
    • (2015) ICCV
    • Caicedo, J.1    Lazebnik, S.2
  • 12
    • 77955989314 scopus 로고    scopus 로고
    • Cross-dataset action detection
    • L. Cao, Z. Liu, and T. S. Huang. Cross-dataset action detection. In CVPR, 2010.
    • (2010) CVPR
    • Cao, L.1    Liu, Z.2    Huang, T.S.3
  • 14
    • 84957029470 scopus 로고    scopus 로고
    • Minds eye: A recurrent visual representation for image caption generation
    • X. Chen and C. L. Zitnick. Minds eye: A recurrent visual representation for image caption generation. CVPR, 2015.
    • (2015) CVPR
    • Chen, X.1    Zitnick, C.L.2
  • 15
    • 1142285426 scopus 로고    scopus 로고
    • Gender differences in three dimensional gait analysis data from 98 healthy Korean adults
    • S. Cho, J. Park, and O. Kwon. Gender differences in three dimensional gait analysis data from 98 healthy korean adults. Clinical biomechanics, 2004.
    • (2004) Clinical Biomechanics
    • Cho, S.1    Park, J.2    Kwon, O.3
  • 19
    • 84931572590 scopus 로고    scopus 로고
    • Deep feature learning with relative distance comparison for person reidentification
    • S. Ding, L. Lin, G. Wang, and H. Chao. Deep feature learning with relative distance comparison for person reidentification. Pattern Recognition, 2015.
    • (2015) Pattern Recognition
    • Ding, S.1    Lin, L.2    Wang, G.3    Chao, H.4
  • 22
    • 77955997115 scopus 로고    scopus 로고
    • Person re-identification by symmetry-driven accumulation of local features
    • M. Farenzena, L. Bazzani, A. Perina, V. Murino, and M. Cristani. Person re-identification by symmetry-driven accumulation of local features. In CVPR, 2010.
    • (2010) CVPR
    • Farenzena, M.1    Bazzani, L.2    Perina, A.3    Murino, V.4    Cristani, M.5
  • 23
    • 33749259827 scopus 로고    scopus 로고
    • Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks
    • A. Graves, S. Fernández, F. Gomez, and J. Schmidhuber. Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks. In ICML, 2006.
    • (2006) ICML
    • Graves, A.1    Fernández, S.2    Gomez, F.3    Schmidhuber, J.4
  • 24
    • 70349996595 scopus 로고    scopus 로고
    • Viewpoint invariant pedestrian recognition with ensemble localized features
    • D. Gray and H. Tao. Viewpoint invariant pedestrian recognition with ensemble localized features. In ECCV. 2008.
    • (2008) ECCV
    • Gray, D.1    Tao, H.2
  • 25
  • 26
    • 33644851749 scopus 로고    scopus 로고
    • Individual recognition using gait energy image
    • J. Han and B. Bhanu. Individual recognition using gait energy image. PAMI, 2006.
    • (2006) PAMI
    • Han, J.1    Bhanu, B.2
  • 28
    • 84871975250 scopus 로고    scopus 로고
    • 2. 5d gait biometrics using the depth gradient histogram energy image
    • M. Hofmann, S. Bachmann, and G. Rigoll. 2. 5d gait biometrics using the depth gradient histogram energy image. In Biometrics. IEEE, 2012.
    • (2012) Biometrics. IEEE
    • Hofmann, M.1    Bachmann, S.2    Rigoll, G.3
  • 29
    • 78651073579 scopus 로고    scopus 로고
    • Gait recognition using linear discriminant analysis with artificial walking conditions
    • X. Huang and N. V. Boulgouris. Gait recognition using linear discriminant analysis with artificial walking conditions. In ICIP, 2010.
    • (2010) ICIP
    • Huang, X.1    Boulgouris, N.V.2
  • 31
    • 84903127719 scopus 로고    scopus 로고
    • Human3. 6m: Large scale datasets and predictive methods for 3d human sensing in natural environments
    • C. Ionescu, D. Papava, V. Olaru, and C. Sminchisescu. Human3. 6m: Large scale datasets and predictive methods for 3d human sensing in natural environments. PAMI, 2014.
    • (2014) PAMI
    • Ionescu, C.1    Papava, D.2    Olaru, V.3    Sminchisescu, C.4
  • 33
    • 84870183903 scopus 로고    scopus 로고
    • 3d convolutional neural networks for human action recognition
    • S. Ji, W. Xu, M. Yang, and K. Yu. 3d convolutional neural networks for human action recognition. PAMI, 2013.
    • (2013) PAMI
    • Ji, S.1    Xu, W.2    Yang, M.3    Yu, K.4
  • 36
    • 84876231242 scopus 로고    scopus 로고
    • Imagenet classification with deep convolutional neural networks
    • A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 2012.
    • (2012) NIPS
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.E.3
  • 37
    • 84878163571 scopus 로고    scopus 로고
    • Color invariants for person reidentification
    • I. Kviatkovsky, A. Adam, and E. Rivlin. Color invariants for person reidentification. PAMI, 2013.
    • (2013) PAMI
    • Kviatkovsky, I.1    Adam, A.2    Rivlin, E.3
  • 38
    • 24944451092 scopus 로고    scopus 로고
    • On space-time interest points
    • I. Laptev. On space-time interest points. IJCV, 2005.
    • (2005) IJCV
    • Laptev, I.1
  • 40
    • 84887369602 scopus 로고    scopus 로고
    • Locally aligned feature transforms across views
    • W. Li and X. Wang. Locally aligned feature transforms across views. In CVPR, 2013.
    • (2013) CVPR
    • Li, W.1    Wang, X.2
  • 41
    • 84911383794 scopus 로고    scopus 로고
    • Deepreid: Deep filter pairing neural network for person re-identification
    • W. Li, R. Zhao, T. Xiao, and X. Wang. Deepreid: Deep filter pairing neural network for person re-identification. In CVPR, 2014.
    • (2014) CVPR
    • Li, W.1    Zhao, R.2    Xiao, T.3    Wang, X.4
  • 42
    • 0033284915 scopus 로고    scopus 로고
    • Object recognition from local scale-invariant features
    • D. Lowe. Object recognition from local scale-invariant features. In ICCV, 1999.
    • (1999) ICCV
    • Lowe, D.1
  • 43
    • 84959874994 scopus 로고    scopus 로고
    • Effective approaches to attention-based neural machine translation
    • M. T. Luong, H. Pham, and C. D. Manning. Effective approaches to attention-based neural machine translation. EMNLP, 2015.
    • (2015) EMNLP
    • Luong, M.T.1    Pham, H.2    Manning, C.D.3
  • 45
    • 84876276096 scopus 로고    scopus 로고
    • Stacked convolutional auto-encoders for hierarchical feature extraction
    • Springer
    • J. Masci, U. Meier, D. Cireşan, and J. Schmidhuber. Stacked convolutional auto-encoders for hierarchical feature extraction. In ICANN. Springer, 2011.
    • (2011) ICANN
    • Masci, J.1    Meier, U.2    Cireşan, D.3    Schmidhuber, J.4
  • 46
    • 0028577362 scopus 로고
    • Gender discrimination in biological motion displays based on dynamic cues
    • G. Mather and L. Murdoch. Gender discrimination in biological motion displays based on dynamic cues. Biological Sciences, 1994.
    • (1994) Biological Sciences
    • Mather, G.1    Murdoch, L.2
  • 47
    • 84938228349 scopus 로고    scopus 로고
    • 3d convolutional neural networks for landing zone detection from lidar
    • D. Maturana and S. Scherer. 3d convolutional neural networks for landing zone detection from lidar. In ICRA, 2015.
    • (2015) ICRA
    • Maturana, D.1    Scherer, S.2
  • 48
    • 84958159870 scopus 로고    scopus 로고
    • Voxnet: A 3d convolutional neural network for real-time object recognition
    • D. Maturana and S. Scherer. Voxnet: A 3d convolutional neural network for real-time object recognition. In IROS, 2015.
    • (2015) IROS
    • Maturana, D.1    Scherer, S.2
  • 49
    • 84866651553 scopus 로고    scopus 로고
    • Pcca: A new approach for distance learning from sparse pairwise constraints
    • A. Mignon and F. Jurie. Pcca: A new approach for distance learning from sparse pairwise constraints. In CVPR, 2012.
    • (2012) CVPR
    • Mignon, A.1    Jurie, F.2
  • 50
    • 84937959846 scopus 로고    scopus 로고
    • Recurrent models of visual attention
    • V. Mnih, N. Heess, A. Graves, et al. Recurrent models of visual attention. In NIPS, 2014.
    • (2014) NIPS
    • Mnih, V.1    Heess, N.2    Graves, A.3
  • 51
    • 84881343966 scopus 로고    scopus 로고
    • Multimodal person re-identification using rgb-d sensors and a transient identification database
    • A. Mogelmose, T. B. Moeslund, and K. Nasrollahi. Multimodal person re-identification using rgb-d sensors and a transient identification database. In Biometrics and Forensics. IEEE, 2013.
    • (2013) Biometrics and Forensics. IEEE
    • Mogelmose, A.1    Moeslund, T.B.2    Nasrollahi, K.3
  • 52
    • 84929223133 scopus 로고    scopus 로고
    • 3d reconstruction of freely moving persons for re-identification with a depth sensor
    • M. Munaro, A. Basso, A. Fossati, L. Van Gool, and E. Menegatti. 3d reconstruction of freely moving persons for re-identification with a depth sensor. In ICRA, 2014.
    • (2014) ICRA
    • Munaro, M.1    Basso, A.2    Fossati, A.3    Van Gool, L.4    Menegatti, E.5
  • 54
    • 84929207716 scopus 로고    scopus 로고
    • A feature-based approach to people re-identification using skeleton keypoints
    • M. Munaro, S. Ghidoni, D. T. Dizmen, and E. Menegatti. A feature-based approach to people re-identification using skeleton keypoints. In ICRA, 2014.
    • (2014) ICRA
    • Munaro, M.1    Ghidoni, S.2    Dizmen, D.T.3    Menegatti, E.4
  • 55
    • 85017484159 scopus 로고    scopus 로고
    • Person identification using full-body motion and anthropometric biometrics from kinect videos
    • B. C. Munsell, A. Temlyakov, C. Qu, and S. Wang. Person identification using full-body motion and anthropometric biometrics from kinect videos. In ECCV, 2012.
    • (2012) ECCV
    • Munsell, B.C.1    Temlyakov, A.2    Qu, C.3    Wang, S.4
  • 58
    • 84887375927 scopus 로고    scopus 로고
    • Hon4d: Histogram of oriented 4d normals for activity recognition from depth sequences
    • O. Oreifej and Z. Liu. Hon4d: Histogram of oriented 4d normals for activity recognition from depth sequences. In CVPR, 2013.
    • (2013) CVPR
    • Oreifej, O.1    Liu, Z.2
  • 61
    • 84897766568 scopus 로고    scopus 로고
    • Person re-identification with a ptz camera: An introductory study
    • P. Salvagnini, L. Bazzani, M. Cristani, and V. Murino. Person re-identification with a ptz camera: An introductory study. In ICIP, 2013.
    • (2013) ICIP
    • Salvagnini, P.1    Bazzani, L.2    Cristani, M.3    Murino, V.4
  • 62
    • 84922556677 scopus 로고    scopus 로고
    • Stacked autoencoders for unsupervised feature learning and multiple organ detection in a pilot study using 4d patient data
    • H. C. Shin, M. R. Orton, D. J. Collins, S. J. Doran, and M. O. Leach. Stacked autoencoders for unsupervised feature learning and multiple organ detection in a pilot study using 4d patient data. PAMI, 2013.
    • (2013) PAMI
    • Shin, H.C.1    Orton, M.R.2    Collins, D.J.3    Doran, S.J.4    Leach, M.O.5
  • 66
    • 30144444418 scopus 로고    scopus 로고
    • Matching shape sequences in video with applications in human movement analysis
    • A. Veeraraghavan, A. K. Roy-Chowdhury, and R. Chellappa. Matching shape sequences in video with applications in human movement analysis. PAMI, 2005.
    • (2005) PAMI
    • Veeraraghavan, A.1    Roy-Chowdhury, A.K.2    Chellappa, R.3
  • 67
    • 84871393884 scopus 로고    scopus 로고
    • Robust 3d action recognition with random occupancy patterns
    • J. Wang, Z. Liu, J. Chorowski, Z. Chen, and Y. Wu. Robust 3d action recognition with random occupancy patterns. In ECCV. 2012.
    • (2012) ECCV
    • Wang, J.1    Liu, Z.2    Chorowski, J.3    Chen, Z.4    Wu, Y.5
  • 69
    • 0000337576 scopus 로고
    • Simple statistical gradient-following algorithms for connectionist reinforcement learning
    • R. J. Williams. Simple statistical gradient-following algorithms for connectionist reinforcement learning. Machine learning, 1992.
    • (1992) Machine Learning
    • Williams, R.J.1
  • 70
    • 84959255406 scopus 로고    scopus 로고
    • The application of two-level attention models in deep convolutional neural network for fine-grained image classification
    • T. Xiao, Y. Xu, K. Yang, J. Zhang, Y. Peng, and Z. Zhang. The application of two-level attention models in deep convolutional neural network for fine-grained image classification. CVPR, 2015.
    • (2015) CVPR
    • Xiao, T.1    Xu, Y.2    Yang, K.3    Zhang, J.4    Peng, Y.5    Zhang, Z.6
  • 73
    • 84959243528 scopus 로고    scopus 로고
    • Deep metric learning for practical person re-identification
    • D. Yi, Z. Lei, and S. Z. Li. Deep metric learning for practical person re-identification. ICPR, 2014.
    • (2014) ICPR
    • Yi, D.1    Lei, Z.2    Li, S.Z.3
  • 75
    • 84898773205 scopus 로고    scopus 로고
    • The moving pose: An efficient 3d kinematics descriptor for low-latency action recognition and detection
    • M. Zanfir, M. Leordeanu, and C. Sminchisescu. The moving pose: An efficient 3d kinematics descriptor for low-latency action recognition and detection. In ICCV, 2013.
    • (2013) ICCV
    • Zanfir, M.1    Leordeanu, M.2    Sminchisescu, C.3
  • 76
    • 85009899017 scopus 로고    scopus 로고
    • Visualizing and understanding convolutional networks
    • M. D. Zeiler and R. Fergus. Visualizing and understanding convolutional networks. In ECCV. 2014.
    • (2014) ECCV
    • Zeiler, M.D.1    Fergus, R.2
  • 78
    • 84887375390 scopus 로고    scopus 로고
    • Unsupervised salience learning for person re-identification
    • R. Zhao, W. Ouyang, and X. Wang. Unsupervised salience learning for person re-identification. In CVPR, 2013.
    • (2013) CVPR
    • Zhao, R.1    Ouyang, W.2    Wang, X.3
  • 79
    • 84911428050 scopus 로고    scopus 로고
    • Learning mid-level filters for person re-identification
    • R. Zhao, W. Ouyang, and X. Wang. Learning mid-level filters for person re-identification. In CVPR, 2014.
    • (2014) CVPR
    • Zhao, R.1    Ouyang, W.2    Wang, X.3
  • 81
    • 84887359177 scopus 로고    scopus 로고
    • Separating signal from noise using patch recurrence across scales
    • M. Zontak, I. Mosseri, and M. Irani. Separating signal from noise using patch recurrence across scales. In CVPR, 2013.
    • (2013) CVPR
    • Zontak, M.1    Mosseri, I.2    Irani, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.