Exploiting amodal cues for robot perception

International Journal of Humanoid Robotics

Volumn 2, Issue 2, 2005, Pages 125-143

  ARSENIO, ARTUR M ^a   FITZPATRICK, PAUL M ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Cross modal perception; humanoid robotics; machine learning; object recognition; object segmentation

Indexed keywords

ANTHROPOMORPHIC ROBOTS; IMAGE SEGMENTATION; LEARNING SYSTEMS; ROBOTICS;

CROSS-MODAL; CROSS-MODAL PERCEPTION; HUMANOID ROBOT; HUMANOID ROBOTICS; MOVING OBJECTS; OBJECTS RECOGNITION; OBJECTS SEGMENTATION; PHYSICAL ABRASION; ROBOT PERCEPTION; SOUND LOCALIZATION;

OBJECT RECOGNITION;

EID: 38949159224     PISSN: 02198436     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219843605000429     Document Type: Article

References (14)

1. R. A. Brooks, C. Breazeal, M. Marjanovic and B. Scassellati, The Cog project: Building a humanoid robot, Lect. Notes Comput. Sci. 1562, 52-87 (1999).
2. L. E. Bahrick, The development of perception in a multimodal environment, in Theories of Infant Development, eds. G. Bremner and A. Slater (Blackwell Publishing, Malden, MA, 2004), pp. 90-120.
3. P. Fitzpatrick, Object lesson: Discovering and learning to recognize objects, in Proc. 3rd. Int. Conf. Humanoid Robots, Karlsruhe, Germany (2003).
4. D. J. Lewkowicz, Learning and discrimination of audiovisual events in human infants: The hierarchical relation between intersensory temporal synchrony and rhythmic pattern cues, Dev. Psychol. 39(5), 795-804 (2003).
5. R. Polana and R. C. Nelson, Detection and recognition of periodic, non-rigid motion, Int. J. Comput. Vision 23(3), 261-282 (1997).
6. A. Arsenio, Embodied vision Perceiving objects from actions, IEEE Int. Workshop Human-Robot Interactive Communication (RO-MAN2003),Westin San Francisco Airport Hotel, USA (31 October-2 November 2003).
7. P. Fitzpatrick, From first contact to close encounters: A developmentally deep perceptual system for a humanoid robot, Ph.D. thesis, MIT, Cambridge, MA, 2003.
8. E. Krotkov, R. Klatzky and N. Zumel, Robotic perception of material: Experiments with shape-invariant acoustic measures of material type, in Experimental Robotics IV, eds. O. Khatib and K. Salisbury (Springer-Verlag, Berlin, 1996).
9. A. M. Arsenio, An embodied approach to perceptual grouping, accepted to the IEEE CVPR Workshop on Perceptual Organization in Computer Vision (2004).
10. J. Shi and C. Tomasi, Good features to track, in Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR1994) Seattle, USA (June, 1994), pp. 593-600.
11. A.M. Arsenio, Map building from human-computer interactions, accepted to the IEEE CVPR Workshop on Real-time Vision for Human Computer Interaction (2004).
12. M. Turk and A. Pentland, Face recognition using eigenfaces, in IEEE Int. Conf. Computer Vision and Pattern Recognition (CVPR) (1991).
13. J. A. Bashford, B. S. Brubaker and R. M. Warren, Cross-modal enhancement of repetition detection for very long period recycling frozen noise, J. Acoust. Soc. Am. 93(4), 2315 (1993).
14. C. Kaernbach, Temporal and spectral basis of the features perceived in repeated noise, J. Acoust. Soc. Am. 94(1), 91-97 (1993).