Saliency-based identification and recognition of pointed-at objects

IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings

Volumn , Issue , 2010, Pages 4638-4643

  Schauerte, Boris ^a   Richarz, Jan ^a   Fink, Gernot A ^a  

^a TU DORTMUND UNIVERSITY   (Germany)

Author keywords

Active pan tilt zoom camera; Joint attention; Object detection and learning; Pointing gestures; Saliency

Indexed keywords

JOINT ATTENTION; OBJECT DETECTION; PAN-TILT-ZOOM CAMERA; POINTING GESTURES; SALIENCY;

CAMERAS; INTELLIGENT ROBOTS; VIDEO CAMERAS; VISUAL COMMUNICATION; VISUALIZATION;

OBJECT RECOGNITION;

EID: 78651476631     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IROS.2010.5649430     Document Type: Conference Paper

References (45)

1. M. Louwerse and A. Bangerter, "Focusing attention with deictic gestures and linguistic expressions," in Proc. Ann. Conf. Cog. Sci. Soc., 2005.
2. S. Bock, P. Dicke, and P. Thier, "How precise is gaze following in humans?" Vis. Res., vol. 48, pp. 946-957, 2008.
3. M. Tomasello, Constructing a Language: A Usage-Based Theory of Language Acquisition. Harvard University Press, 2003.
4. F. Kaplan and V. Hafner, "The challenges of joint attention," Interaction Studies, vol. 7, pp. 135-169, 2006.
5. P. Mundy and L. Newell, "Attention, joint attention, and social cognition," Curr. Dir. Psychol. Sci., vol. 16, pp. 269-274, 2007.
6. M. Staudte and M. W. Crocker, "Visual attention in spoken humanrobot interaction," in HRI, 2009.
7. G. Heidemann, R. Rae, et al., "Integrating context-free and contextdependent attentional mechanisms for gestural object reference," Mach. Vis. Appl., vol. 16, pp. 64-73, 2004.
8. N. Butko, L. Zhang, et al., "Visual saliency model for robot cameras," in ICRA, 2008.
9. L. Elazary and L. Itti, "Interesting objects are visually salient," J. Vis., vol. 8, pp. 1-15, 2008.
10. J. Ruesch, M. Lopes, et al., "Multimodal saliency-based bottom-up attention: A framework for the humanoid robot iCub," in ICRA, 2008.
11. K. Gao, S. Lin, et al., "Attention model based SIFT keypoints filtration for image retrieval," in Proc. Int. Conf. Comp. Inf. Sci., 2008.
12. B. Schauerte, J. Richarz, et al., "Multi-modal and multi-camera attention in smart environments," in Proc. Int. Conf. Multimodal Interfaces, 2009.
13. S. Frintrop, E. Rome, and H. I. Christensen, "Computational visual attention systems and their cognitive foundation: A survey," ACM Trans. Applied Perception, vol. 7, 2010.
14. D. Meger, P.-E. Forssén, et al., "Curious George: An attentive semantic robot," in IROS Workshop: From sensors to human spatial concepts, 2007.
15. Y. Sun and R. Fisher, "Object-based visual attention for computer vision," Artificial Intelligence, vol. 146, pp. 77-123, 2003.
16. F. Orabona, G. Metta, and G. Sandini, "Object-based visual attention: a model for a behaving robot," in CVPR Workshop: Attention and Performance in Computational Vision, 2005.
17. X. Hou and L. Zhang, "Saliency detection: A spectral residual approach," in CVPR, 2007.
18. C. Guo, Q. Ma, and L. Zhang, "Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform," in CVPR, 2008.
19. A. Oppenheim and J. Lim, "The importance of phase in signals," Proceedings of the IEEE, vol. 69, pp. 529-541, 1981.
20. D. Walther, U. Rutishauser, et al., "Selective visual attention enables learning and recognition of multiple objects in cluttered scenes," Comp. Vis. Image Understand., vol. 100, pp. 41-63, 2005.
21. K. Welke, T. Asfour, and R. Dillmann, "Active multi-view object search on a humanoid head," in ICRA, 2009.
22. T. Tuytelaars and K. Mikolajczyk, "Local invariant feature detectors: A survey," Found. Trends Comp. Graph. Vis., vol. 3, pp. 177-280, 2007.
23. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," Int. J. Comp. Vis., vol. 60, pp. 91-110, 2004.
24. D. Figueira, M. Lopes, et al., "From pixels to objects: Enabling a spatial model for humanoid social robots," in ICRA, 2009.
25. M. Doniec, G. Sun, and B. Scassellati, "Active learning of joint attention," in Humanoids, 2006.
26. Y. Nagai, K. Hosoda, et al., "A constructive model for the development of joint attention," Connection Sci., vol. 15, pp. 211-229, 2003.
27. J. Triesch, C. Teuscher, et al., "Gaze following: why (not) learn it?" Dev. Sci., vol. 9, pp. 125-147, 2006.
28. H. Kozima and A. Ito, "Towards language acquisition by an attentionsharing robot," in New Methods in Language Processing and Computational Natural Language Learning, D. Powers, Ed. ACL, 1998, pp. 245-246.
29. O. Sugiyama, T. Kanda, et al., "Three-layered draw-attention model for communication robots with pointing gesture and verbal cues," J. Robot. Soc. Japan, vol. 24, pp. 964-975, 2006.
30. -, "Natural deictic communication with humanoid robots," in IROS, 2007.
31. M. W. Hoffman, D. B. Grimes, et al., "A probabilistic model of gaze imitation and shared attention," Neural Networks, vol. 19, pp. 299-310, 2006.
32. M. Katzenmaier, R. Stiefelhagen, and T. Schultz, "Identifying the addressee in human-human-robot interactions based on head pose and speech," in Proc. Int. Conf. Multimodal Interfaces, 2004.
33. R. Kehl and L. Van Gool, "Real-time pointing gesture recognition for an immersive environment," in Proc. Int. Conf. Automatic Face and Gesture Rec., 2004.
34. C.-Y. Chien, C.-L. Huang, and C.-M. Fu, "A vision-based real-time pointing arm gesture tracking and recognition system," in Proc. Int. Conf. Multimedia and Expo, 2007.
35. C.-B. Park, M.-C. Roh, and S.-W. Lee, "Real-time 3D pointing gesture recognition in mobile space," in Proc. Int. Conf. Automatic Face and Gesture Rec., 2008.
36. E. Sato, T. Yamaguchi, and F. Harashima, "Natural interface using pointing behavior for human-robot gestural interaction," IEEE Trans. Ind. Electron., vol. 54, pp. 1105-1112, 2007.
37. J. Schmidt, N. Hofemann, et al., "Interacting with a mobile robot: Evaluating gestural object references," in IROS, 2008.
38. Y. Tamura, M. Sugi, et al., "Target identification through human pointing gesture based on human-adaptive approach," J. Robot. Mechatron., vol. 20, pp. 515-525, 2008.
39. K. Nickel and R. Stiefelhagen, "Visual recognition of pointing gestures for human-robot interaction," Image Vis. Comp., vol. 25, pp. 1875-1884, 2007.
40. J. Richarz, T. Plötz, and G. A. Fink, "Real-time detection and interpretation of 3D deictic gestures for interaction with an intelligent environment," in ICPR, 2008.
41. Y. Jia, S. Li, and Y. Liu, "Tracking pointing gesture in 3d space for wearable visual interfaces," in Proc. Int. Workshop on Human- Centered Multimedia, 2007.
42. N. Hofemann, J. Fritsch, and G. Sagerer, "Recognition of deictic gestures with context," in Proc. DAGM Symp. Pat. Rec., 2004.
43. A. Kranstedt, A. Lücking, et al., "Deixis: How to determine demonstrated objects using a pointing cone," in Proc. Int. Gesture Workshop, 2006.
44. J. Matas, O. Chum, et al., "Robust wide-baseline stereo from maximally stable extremal regions," Image Vis. Comp., vol. 22, pp. 761-767, 2004.
45. M. A. McDowell, C. D. Fryar, et al., "Anthropometric reference data for children and adults: United states, 2003-2006," National Health Statistics Reports, Tech. Rep., 2008.