Clothes Change Detection Using the Kinect Sensor

Dimitris Sgouropoulos, Theodoros Giannakopoulos, Sergios Petridis, Stavros Perantonis, Antonis Korakis

Abstract

This paper describes a methodology for detecting when a human has changed clothes. Changing clothes is a basic activity of daily living which makes the methodology valuable for tracking the functional status of elderly people, in the context of a non-contract unobtrusive monitoring system. Our approach uses Kinect and the OpenNI SDK, along with a workflow of basic image analysis steps. Evaluation has been conducted on a set of real recordings under various illumination conditions, which is publicly available along with the source code of the proposed system at http://users.iit.demokritos.gr/ tyianak/ClothesCode.html.

References

  1. (2011). Microsoft kinect sensor. Online available: http://www.microsoft.com/en-us/kinectforwindows/. Accessed April 1, 2013.
  2. Bossard, L., Dantone, M., Leistner, C., Wengert, C., Quack, T., and Gool, L. V. (2013). Apparel classification with style. In Computer Vision-ACCV 2012, pages 321- 335. Springer.
  3. Chen, H., Gallagher, A., and Girod, B. (2012). Describing clothing by semantic attributes. In Computer VisionECCV 2012, pages 609-623. Springer.
  4. Collin, C. and Wade, D. (1988). The barthel adl index: a standard measure of physical disability? Disability & Rehabilitation, 10(2):64-67.
  5. Collin, C., Wade, D., Davies, S., and Horne, V. (1988). The barthel adl index: a reliability study. Disability & Rehabilitation, 10(2):61-63.
  6. Fleury, A., Vacher, M., and Noury, N. (2010). Svm-based multimodal classification of activities of daily living in health smart homes: sensors, algorithms, and first experimental results. Information Technology in Biomedicine, IEEE Transactions on, 14(2):274-283.
  7. Funt, B., Cardei, V., and Barnard, K. (1996). Learning color constancy. In IS&T/SID Fourth Color Imaging Conference, pages 58-60.
  8. Kalantidis, Y., Kennedy, L., and Li, L.-J. (2013). Getting the look: clothing recognition and segmentation for automatic product suggestions in everyday photos. In Proceedings of the 3rd conference on International conference on multimedia retrieval, pages 105-112. ACM.
  9. Liu, S., Feng, J., Song, Z., Zhang, T., Lu, H., Xu, C., and Yan, S. (2012a). Hi, magic closet, tell me what to wear! In Proceedings of the 20th international conference on Multimedia, pages 619-628. ACM.
  10. Liu, S., Song, Z., Liu, G., Xu, C., Lu, H., and Yan, S. (2012b). Street-to-shop: Cross-scenario clothing retrieval via parts alignment and auxiliary set. In Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, pages 3330-3337. IEEE.
  11. Maitin-Shepard, J., Cusumano-Towner, M., Lei, J., and Abbeel, P. (2010). Cloth grasp point detection based on multiple-view geometric cues with application to robotic towel folding. In Robotics and Automation (ICRA), 2010 IEEE International Conference on, pages 2308-2315. IEEE.
  12. Ramisa, A., Alenya, G., Moreno-Noguer, F., and Torras, C. (2012). Using depth and appearance features for informed robot grasping of highly wrinkled clothes. In Robotics and Automation, International Conference on, pages 1703-1708. IEEE.
  13. Self-maintenance, P. (1969). Assessment of older people: self-maintaining and instrumental activities of daily living.
  14. Shotton, J., Sharp, T., Kipman, A., Fitzgibbon, A., Finocchio, M., Blake, A., Cook, M., and Moore, R. (2013). Real-time human pose recognition in parts from single depth images. Communications of the ACM, 56(1):116-124.
  15. Stikic, M., Huynh, T., Laerhoven, K. V., and Schiele, B. (2008). Adl recognition based on the combination of rfid and accelerometer sensing. In Pervasive Computing Technologies for Healthcare, 2008, pages 258- 263. IEEE.
  16. Willimon, B., Birchfleld, S., and Walker, I. (2011). Classification of clothing using interactive perception. In Robotics and Automation (ICRA), 2011 IEEE International Conference on, pages 1862-1868. IEEE.
  17. Willimon, B., Walker, I., and Birchfield, S. (2013). A new approach to clothing classification using midlevel layers. In Proceedings of the International Conference on Robotics and Automation (ICRA).
  18. Xia, L., Chen, C.-C., and Aggarwal, J. (2011). Human detection using depth information by kinect. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2011 IEEE Computer Society Conference on, pages 15-22. IEEE.
  19. Zhang, Z. (2012). Microsoft kinect sensor and its effect. MultiMedia, IEEE, 19(2):4-10.
Download


Paper Citation


in Harvard Style

Sgouropoulos D., Giannakopoulos T., Petridis S., Perantonis S. and Korakis A. (2014). Clothes Change Detection Using the Kinect Sensor . In Proceedings of the 11th International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2014) ISBN 978-989-758-046-8, pages 85-89. DOI: 10.5220/0005001200850089


in Bibtex Style

@conference{sigmap14,
author={Dimitris Sgouropoulos and Theodoros Giannakopoulos and Sergios Petridis and Stavros Perantonis and Antonis Korakis},
title={Clothes Change Detection Using the Kinect Sensor},
booktitle={Proceedings of the 11th International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2014)},
year={2014},
pages={85-89},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005001200850089},
isbn={978-989-758-046-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Signal Processing and Multimedia Applications - Volume 1: SIGMAP, (ICETE 2014)
TI - Clothes Change Detection Using the Kinect Sensor
SN - 978-989-758-046-8
AU - Sgouropoulos D.
AU - Giannakopoulos T.
AU - Petridis S.
AU - Perantonis S.
AU - Korakis A.
PY - 2014
SP - 85
EP - 89
DO - 10.5220/0005001200850089