From saliency to eye gaze: Embodied visual selection for a pan-tilt-based robotic head

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6938 LNCS, Issue PART 1, 2011, Pages 135-146

  Mancas, Matei ^a   Pirri, Fiora ^b   Pizzoli, Matia ^b  

^a UNIVERSITY OF MONS   (Belgium)

^b SAPIENZA UNIVERSITY OF ROME   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE VISION; EYE-GAZE; GAZE BEHAVIOR; MODEL ESTIMATES; PAN-TILT CAMERA; PHYSICAL SYSTEMS; REAL TIME; ROBOTIC HEAD; SALIENCY MAP; SMOOTH PURSUIT; VIDEO SEQUENCES; VISUAL SELECTION; VISUAL SENSING;

COMPUTER VISION; DYNAMICS; ROBOTICS;

EYE MOVEMENTS;

EID: 80053345848     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-24028-7_13     Document Type: Conference Paper

References (17)

1. Treisman, A., Gelade, G.: A feature-integration theory of attention. Cognitive Psychology 12, 97-136 (1980)
2. Tsotsos, J., Culhane, S., Wai, W., Lai, Y., Davis, N., Nuflo, F.: Modeling visual attention via selective tuning. Artifical Intelligence 78, 507-547 (1995)
3. Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE TPAMI 20, 1254-1259 (1998)
4. Butko, N., Movellan, J.: Infomax control of eye movements. IEEE Transactions on Autonomous Mental Development 2, 91-107 (2010)
5. Koch, C., Ullman, S.: Shifts in selective visual-attention: towards the underlying neural circuitry. Hum. Neurobiol. 4, 219-227 (1985)
6. Mahadevan, V., Vasconcelos, N.: Spatiotemporal saliency in dynamic scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence 32, 171-177 (2010)
7. Kowler, E.: Eye movements: The past 25years. Vision Research, 1-27 (2011)
8. Farnebäck, G.: Two-frame motion estimation based on polynomial expansion. In: Bigun, J., Gustavsson, T. (eds.) SCIA 2003. LNCS, vol. 2749, pp. 363-370. Springer, Heidelberg (2003)
9. Mancas, M., Riche, N., Leroy, J., Gosselin, B.: Abnormal motion selection in crowds using bottom-up saliency. In: Proc. of the ICIP (2011)
10. Sauter, D., Martin, B., Di Renzo, N., Vomscheid, C.: Analysis of eye tracking movements using innovations generated by a kalman filter. Medical and Biological Engineering and Comp. (1991)
11. Engbert, R., Kliegl, R.: Microsaccades uncover the orientation of covert attention. Vision Research 43, 1035-1045 (2003)
12. Komogortsev, O., Khan, J.I.: Eye movement prediction by kalman filter with integrated linear horizontal oculomotor plant mechanical model. In: ETRA, pp. 229-236 (2008)
13. Blom, H., Bar-Shalom, Y.: The interactive multiple model algorithm for system with markovian switching coefficients. IEEE Trans. on Automatic Control 33, 780-783 (1988)
14. Julier, S.J., Jeffrey, Uhlmann, K.: Unscented filtering and nonlinear estimation. Proceedings of the IEEE (2004)
15. Julier, S.J., Uhlmann, J.K.: A new extension of the kalman filter to nonlinear systems. In: Proceedings of AeroSense: The 11th International Symposium on Aerospace/Defense Sensing, Simulation and Controls, pp. 182-193 (1997)
16. Wan, E., van der Merwe, R.: The unscented kalman filter for nonlinear estimation. In: Proc. of the Symposium on Adaptive Systems for Signal Processing, Communication and Control (2000)
17. Singer, R.A.: Estimating optimal tracking filter performance for manned maneuvering targets. IEEE Transactions on Aerospace and Electrictronic Systems (1970)