메뉴 건너뛰기




Volumn 3, Issue , 2008, Pages 1402-1408

A fast data collection and augmentation procedure for object recognition

Author keywords

Computer vision; Data driven artificial intelligence; Robotics: application

Indexed keywords

DATA COLLECTION METHODS; DATA COLLECTIONS; DATA-DRIVEN ARTIFICIAL INTELLIGENCE; EMERGING APPLICATIONS; MOBILE ROBOTICS; OBJECT CLASS RECOGNITIONS; OBJECT RECOGNITION SYSTEMS; OFFICE ENVIRONMENTS; PRACTICAL SOLUTIONS; PROBABILISTIC MODELS; RECOGNITION METHODS; STANDARD PROTOCOLS; TRAINING SETS;

EID: 57749110478     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (21)

References (31)
  • 1
    • 12844249589 scopus 로고    scopus 로고
    • Learning to detect objects in images via a sparse, part-based representation
    • Agarwal, S., and Awan, A. 2004. Learning to detect objects in images via a sparse, part-based representation. IEEE PAMI 26(11):1475-1490.
    • (2004) IEEE PAMI , vol.26 , Issue.11 , pp. 1475-1490
    • Agarwal, S.1    Awan, A.2
  • 2
    • 56749176856 scopus 로고    scopus 로고
    • A local basis representation for estimating human pose from cluttered images
    • Agarwal, A., and Triggs, B. 2006. A local basis representation for estimating human pose from cluttered images. In ACCV.
    • (2006) ACCV
    • Agarwal, A.1    Triggs, B.2
  • 3
    • 33749260356 scopus 로고    scopus 로고
    • Cover trees for nearest neighbor
    • New York, NY, USA: ACM Press
    • Beygelzimer, A.; Kakade, S.; and Langford, J. 2006. Cover trees for nearest neighbor. In ICML. New York, NY, USA: ACM Press.
    • (2006) ICML
    • Beygelzimer, A.1    Kakade, S.2    Langford, J.3
  • 5
    • 33645146449 scopus 로고    scopus 로고
    • Histograms of oriented gradients for human detection
    • Dalal, N., and Triggs, B. 2005. Histograms of oriented gradients for human detection. In CVPR.
    • (2005) CVPR
    • Dalal, N.1    Triggs, B.2
  • 6
    • 33745861631 scopus 로고    scopus 로고
    • Identifying individuals in video by combining generative and discriminative head models
    • Everingham, M., and Zisserman, A. 2005. Identifying individuals in video by combining generative and discriminative head models. In ICCV.
    • (2005) ICCV
    • Everingham, M.1    Zisserman, A.2
  • 7
    • 36849061085 scopus 로고    scopus 로고
    • The 2005 pascal visual object classes challenge
    • Springer-Verlag
    • Everingham, M. e. a. 2006. The 2005 pascal visual object classes challenge. In Machine Learning Challenges. Springer-Verlag.
    • (2006) Machine Learning Challenges
    • Everingham, M.1    e., a.2
  • 8
    • 33144466753 scopus 로고    scopus 로고
    • One-shot learning of object categories
    • Fei-Fei, L.; Fergus, R.; and Perona, P. 2006. One-shot learning of object categories. IEEE PAMI 28(4):594-611.
    • (2006) IEEE PAMI , vol.28 , Issue.4 , pp. 594-611
    • Fei-Fei, L.1    Fergus, R.2    Perona, P.3
  • 9
    • 33745839880 scopus 로고    scopus 로고
    • Learning object categories from google's image search
    • Fergus, R.; Fei-Fei, L.; Perona, P.; and Zisserman, A. 2005. Learning object categories from google's image search. In ICCV.
    • (2005) ICCV
    • Fergus, R.1    Fei-Fei, L.2    Perona, P.3    Zisserman, A.4
  • 10
    • 0041940256 scopus 로고    scopus 로고
    • Object class recognition by unsupervised scale-invariant learning
    • Fergus, R.; Perona, P.; and Zisserman, A. 2003. Object class recognition by unsupervised scale-invariant learning. In CVPR.
    • (2003) CVPR
    • Fergus, R.1    Perona, P.2    Zisserman, A.3
  • 11
    • 57749102234 scopus 로고    scopus 로고
    • Google. 2005. Google image labeler. http://images.google.com/ imagelabeler.
    • (2005) Google image labeler
  • 12
    • 57749111235 scopus 로고    scopus 로고
    • Caltech-256 object category dataset. Technical Report 7694, Caltech
    • Griffin, G.; Holub, A.; and Perona, P. 2007. Caltech-256 object category dataset. Technical Report 7694, Caltech.
    • (2007)
    • Griffin, G.1    Holub, A.2    Perona, P.3
  • 14
    • 5044231640 scopus 로고    scopus 로고
    • Learning methods for generic object recognition with invariance to pose and lighting
    • LeCun, Y.; Huang, F.-J.; and Bottou, L. 2004. Learning methods for generic object recognition with invariance to pose and lighting. In CVPR.
    • (2004) CVPR
    • LeCun, Y.1    Huang, F.-J.2    Bottou, L.3
  • 15
    • 0042441074 scopus 로고    scopus 로고
    • Analyzing appearance and contour based methods for object categorization
    • Leibe, B., and Schiele, B. 2003. Analyzing appearance and contour based methods for object categorization. In CVPR.
    • (2003) CVPR
    • Leibe, B.1    Schiele, B.2
  • 16
    • 31844450882 scopus 로고    scopus 로고
    • High speed obstacle avoidance using monocular vision and reinforcement learning
    • Michels, J.; Saxena, A.; and Ng, A. Y. 2005. High speed obstacle avoidance using monocular vision and reinforcement learning. In ICML.
    • (2005) ICML
    • Michels, J.1    Saxena, A.2    Ng, A.Y.3
  • 17
    • 0030387952 scopus 로고    scopus 로고
    • Real-time focus range sensor
    • Nayar, S. K.; Watanabe, M.; and Noguchi, M. 1996. Real-time focus range sensor. IEEE PAMI 18(12): 1186-1198.
    • (1996) IEEE PAMI , vol.18 , Issue.12 , pp. 1186-1198
    • Nayar, S.K.1    Watanabe, M.2    Noguchi, M.3
  • 18
    • 0003212629 scopus 로고
    • Efficient training of artificial neural networks for autonomous navigation
    • Pomerleau, D. 1991. Efficient training of artificial neural networks for autonomous navigation. Neural Comp 3(1):88-97.
    • (1991) Neural Comp , vol.3 , Issue.1 , pp. 88-97
    • Pomerleau, D.1
  • 19
    • 70350385501 scopus 로고    scopus 로고
    • Toward Category-Level Object Recognition
    • Ponce, J, Hebert, M, Schmid, C, and Zisserman, A, eds, of, Springer
    • Ponce, J.; Hebert, M.; Schmid, C.; and Zisserman, A., eds. 2006. Toward Category-Level Object Recognition, volume 4170 of Lecture Notes in Computer Science. Springer.
    • (2006) Lecture Notes in Computer Science , vol.4170
  • 21
    • 0031672526 scopus 로고    scopus 로고
    • Neural network-based face detection
    • Rowley, H.; Baluja, S.; and Kanade, T. 1998. Neural network-based face detection. IEEE PAMI 20(1):23-38.
    • (1998) IEEE PAMI , vol.20 , Issue.1 , pp. 23-38
    • Rowley, H.1    Baluja, S.2    Kanade, T.3
  • 22
    • 33745835982 scopus 로고    scopus 로고
    • LabelMe: A database and web-based tool for image annotation
    • Technical report, MIT
    • Russell, B. C.; Torralba, A.; Murphy, K. P.; and Freeman, W. T. 2005. LabelMe: a database and web-based tool for image annotation. Technical report, MIT.
    • (2005)
    • Russell, B.C.1    Torralba, A.2    Murphy, K.P.3    Freeman, W.T.4
  • 24
    • 38649089443 scopus 로고    scopus 로고
    • Robotic grasping of novel objects using vision
    • Saxena, A.; Driemeyer, J.; and Ng, A. Y. 2008. Robotic grasping of novel objects using vision. IJRR 27(2).
    • (2008) IJRR , vol.27 , Issue.2
    • Saxena, A.1    Driemeyer, J.2    Ng, A.Y.3
  • 25
    • 50649107659 scopus 로고    scopus 로고
    • Learning 3-d scene structure from a single still image
    • Representation for Recognition 3dRR-07
    • Saxena, A.; Sun, M.; and Ng, A. Y. 2007. Learning 3-d scene structure from a single still image. In ICCV workshop on 3D Representation for Recognition (3dRR-07).
    • (2007) ICCV workshop on , vol.3 D
    • Saxena, A.1    Sun, M.2    Ng, A.Y.3
  • 26
    • 24644511277 scopus 로고    scopus 로고
    • Object recognition with features inspired by visual cortex
    • Serre, T.; Wolf, L.; and Poggio, T. 2005. Object recognition with features inspired by visual cortex. In CVPR.
    • (2005) CVPR
    • Serre, T.1    Wolf, L.2    Poggio, T.3
  • 27
    • 0030389452 scopus 로고    scopus 로고
    • Blue screen matting
    • Smith, A. R., and Blinn, J. F. 1996. Blue screen matting. In SIGGRAPH, 259-268.
    • (1996) SIGGRAPH , pp. 259-268
    • Smith, A.R.1    Blinn, J.F.2
  • 28
    • 5044224293 scopus 로고    scopus 로고
    • Sharing features: Efficient boosting procedures for multiclass object detection
    • Torralba, A.; Murphy, K. P.; and Freeman, W. T. 2004. Sharing features: efficient boosting procedures for multiclass object detection. In CVPR.
    • (2004) CVPR
    • Torralba, A.1    Murphy, K.P.2    Freeman, W.T.3
  • 29
    • 2142812371 scopus 로고    scopus 로고
    • Robust real-time object detection
    • Viola, P., and Jones, M. 2004. Robust real-time object detection. IJCV 57(2).
    • (2004) IJCV , vol.57 , Issue.2
    • Viola, P.1    Jones, M.2
  • 30
    • 33750284902 scopus 로고    scopus 로고
    • Peekaboom: A game for locating objects in images
    • von Ahn, L.; Liu, R.; and Blum, M. 2006. Peekaboom: a game for locating objects in images. In SIGCHI.
    • (2006) SIGCHI
    • von Ahn, L.1    Liu, R.2    Blum, M.3
  • 31
    • 84898993295 scopus 로고    scopus 로고
    • Learning a rare event detection cascade by direct feature selection
    • Wu, J.; Rehg, J.; and Mullin, M. 2004. Learning a rare event detection cascade by direct feature selection. In NIPS.
    • (2004) NIPS
    • Wu, J.1    Rehg, J.2    Mullin, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.