Recognizing complex instrumental activities of daily living using scene information and fuzzy logic

Computer Vision and Image Understanding

Volumn 140, Issue , 2015, Pages 68-82

  Banerjee, Tanvi ^a   Keller, James M ^b   Popescu, Mihail ^b   Skubic, Marjorie ^b  

^a Wright State University   (United States)

^b UNIVERSITY OF MISSOURI   (United States)

Author keywords

Activities of daily living; Activity analysis; Depth images; Eldercare; Fuzzy logic; Image features; Scene understanding

Indexed keywords

HEALTH RISKS; HIDDEN MARKOV MODELS; MARKOV PROCESSES;

ACTIVITIES OF DAILY LIVING; ACTIVITY ANALYSIS; DEPTH IMAGE; ELDERCARE; IMAGE FEATURES; SCENE UNDERSTANDING;

FUZZY LOGIC;

EID: 84941743636     PISSN: 10773142     EISSN: 1090235X     Source Type: Journal    
DOI: 10.1016/j.cviu.2015.04.005     Document Type: Article

References (45)

1. D.G. Lowe. Object recognition from local scale-invariant features, in: Proc. ICCV, Kerkyra, Greece, 1999, pp. 1150-1157.
2. E.E. Stone, M. Skubic Unobtrusive, continuous, in-home gait measurement using the Microsoft Kinect IEEE Trans. Biomed. Eng. 60 10 2013 2925 2932
3. A. Telea An image inpainting technique based on the fast marching method J. Graphics Tools 9 1 2004 23 34
4. F. Clark, S.P. Azen, M. Carlson, D. Mandel, L. LaBree, J. Hay, R. Zemke, J. Jackson, L. Lipson Embedding health promoting changes into the daily lives of independent-living older adults J. Gerontol. Ser. B, Psychol. Sci. Soc. Sci. 56 2001 60 63
5. A. Zisberg, H.M. Young, K. Schepp Development and psychometric testing of the Scale of Older Adults' Routine J. Adv. Nurs. 65 3 2009 672 683
6. L. Chen, C.D. Nugent, H. Wang A knowledge-driven approach to activity recognition in smart homes IEEE Trans. Knowl. Data Eng. 24 6 2012 961 974
7. F. Latfi, B. Lefebvre, C. Descheneaux Ontology-based management of the TeleHealth smart home, dedicated to elderly in loss of cognitive autonomy CEUR Workshop Proceedings 258 2007
8. M.D. Rodríguez, M. Tentori, J. Favela, D. Saldaña-Jimenez, J. García-Vázquez CARe: an ontology for representing context of activity-aware healthcare environments Activity Context Representation 2011
9. C. Graf The Lawton instrumental Activities of Daily Living (IADL) scale. Medsurg. Nurs. 18 2009 315 316
10. D. Anderson, R.H. Luke, J.M. Keller, M. Skubic, M. Rantz, M. Aud Linguistic summarization of video for fall detection using Voxel Person and fuzzy logic Comput. Vis. Image Understanding 113 January (1) 2009 80 89
11. M. Shelkey, M. Wallace Katz index of independence in activities of daily living (ADL) Gerontologist 185 2 1998
12. T. Banerjee, S. Member, J.M. Keller, M. Skubic Resident identification using Kinect depth image data and fuzzy clustering techniques International Conference of the IEEE Engineering in Medicine and Biology Society 2012
13. S. Tang, X. Wang, X. Lv, T.X. Han, J. Keller, Z. He, M. Skubic, S. Lao Histogram of oriented normal vectors for object recognition with a depth sensor The 11th Asian Conference on Computer Vision (ACCV) 2012
14. C. Liu, J. Yuen, A. Torralba SIFT flow: dense correspondence across different scenes and its applications IEEE Trans. Pattern Anal. Mach. Intell. 33 5 2011
15. B. Oehler, J. Stuckler, J. Welle, D. Schulz, S. Behnke Efficient multi-resolution plane segmentation of 3D point clouds Proc. of the International Conference on Intelligent Robotics and Applications (ICIRA) Aachen, Germany 2011 145 156
16. T. Banerjee, J.M. Keller, M. Skubic, Detecting foreground disambiguation of depth images using fuzzy logic, in: 2013 IEEE International Conference on Fuzzy System, pp. 1-7, July 2013.
17. C. Sutton, A. McCallum, L. Getoor, B. Taskar An introduction to conditional random fields for relational learning Introduction to Statistical Relational Learning 2006 MIT Press
18. P.-C. Chung, C.-D. Liu A daily behavior enabled hidden Markov model for human behavior understanding Pattern Recognit 41 May (5) 2008 1572 1580
19. K. Murphy The Bayes net toolbox for MATLAB Comput. Sci. Stat. 33 2001 1024 1034
20. L. Rabiner A tutorial on hidden Markov models and selected applications in speech recognition Proc. IEEE 77 February (2) 1989 257 286
21. J. Bilmes A Gentle Tutorial on the EM Algorithm and Its Application to Parameter Estimation for Gaussian Mixture and Hidden Markov Models 1988 University of Berkley, Technical report ICSI-TR-97-021
22. D. Cook, N. Krishnan, Z. Wemlinger Learning a taxonomy of predefined and discovered activity patterns J. Ambient Intell. Smart Environ. 5 6 2013 621 637
23. E. Nazerfard, D. Cook, Using Bayesian networks for daily activity prediction, in: Twenty-Seventh AAAI, 2013.
24. G. Lavee, E. Rivlin, M. Rudzsky Understanding video events: a survey of methods for automatic interpretation of semantic occurrences in video IEEE Syst. Man Cybern. 39 September (5) 2009 489 504
25. N.T. Nguyen, D.Q. Phung, S. Venkatesh, H. Bui Learning and detecting activities from movement trajectories using the hierarchical hidden Markov models IEEE Computer Society Conference on Computer Vision Pattern Recognition, Washington 2005 955 960
26. T.V. Duong, H.H. Bui, D.Q. Phung, S. Venkatesh Activity recognition and abnormality detection with the switching hidden semi-Markov model Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. 1 2005 838 845
27. S. Gong, H. Buxton On the visual expectations of moving objects Proceedings of the 10th European Conference on Artificial Intelligence (ECAI) 1992 Wiley New York 781 784
28. L. Zadeh Fuzzy sets Inf. Control 8 3 1965 338 353
29. A. Zadeh Outline of a new approach to the analysis of complex systems and decision processes IEEE Trans. Syst. Man Cybern. SMC-3 1973 28 44
30. E.H. Mamdani, S. Assilian An experiment in linguistic synthesis with a fuzzy logic controller Int. J. Man-Mach. Stud. 7 1 1975 1 13
31. J. Sung, C. Ponce, B. Selman, A. Saxena, Unstructured human activity detection from rgbd images, in: ICRA, 2012.
32. D. Brulin, Y. Benezeth, E. Courtial Posture recognition based on fuzzy logic for home monitoring of the elderly IEEE Trans. Inf. Technol. Biomed. 16 5 2012 974 982
33. L.E. Parker, 4-Dimensional local spatio-temporal features for human activity recognition, in: IEEE/RSJ International Conference on Intelligent Robotic System, pp. 2044-2049, September 2011.
34. C. Peters, T. Hermann, S. Wachsmuth, J. Hoey Automatic task assistance for people with cognitive disabilities in brushing teeth - a user study with the TEBRA system ACM Trans. Access. Comput. 5 March (4) 2014 1 34
35. H. Pirsiavash, D. Ramanan Detecting activities of daily living in first-person camera views IEEE Conf. Comput. Vis. Pattern Recognit. June 2012 2847 2854
36. H.S. Koppula, R. Gupta, A. Saxena Learning human activities and object affordances from RGB-D videos Int. J. Robot. Res. 32 July (8) 2013 951 970
37. M. Bengalur, Human activity recognition using body pose features and support vector machine, in: International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp.1970-1975, 22-25 August 2013.
38. C. Zhang, Y. Tian RGB-D camera-based daily living activity recognition J. Comput. Vis. Image Process. 2 December (4) 2012
39. G. Demiris, O. Parker, J. Giger, M. Skubic, M. Rantz Older adults' privacy considerations for vision based recognition methods of eldercare applications Technol. Health Care 17 1 2009 41 48
40. G. Meditskos, S. Dasiopoulou, V. Efstathiou, I. Kompatsiaris Ontology Patterns for Complex Activity Modelling Theory, Practice, and Applications of Rules on the Web Lecture Notes in Computer Science 8035 2013 144 157
41. L. Chen, C. Nugent Ontology-based activity recognition in intelligent pervasive environments Int. J. Web Inf. Syst. 5 4 2009 410 430
42. D. Saldana-Jimenez, M. Rodriguez, J. Garcia-Vazquez, A. Espinoza Elder: an ontology for enabling living independently of risks OTM 2009 Workshops 5872 2009 LNCS 622 627
43. S. Fine, Y. Singer, N. Tishby The hierarchical hidden Markov model: analysis and applications Mach. Learn. 62 1998 41 62
44. H. Lee, J. Kim An HMM-based threshold model approach for gesture recognition IEEE Trans. Pattern Anal. Mach. Intell. 21 October (10) 1999 961 973
45. K. Khoshelham, S. Elberink Accuracy and resolution of Kinect depth data for indoor mapping applications Sensors 12 2 2012 1437 1454