Abstract
Vision is one of the main potential sources of information for robots to understand their surroundings. For a vision system, a clear and close enough view of objects or events, as well as the viewpoint angle can be decisive in obtaining useful features for the vision task. In order to prevent performance drops caused by inefficient camera orientations and positions, manipulating cameras, which falls under the domain of active perception, can be a viable option in a robotic environment.
In this paper, a robotic object detection system is proposed that is capable of determining the confidence of recognition after detecting objects in a camera view. In the event of a low confidence, a secondary camera is moved toward the object and performs an independent detection round. After matching the objects in the two camera views and fusing their classification decisions through a novel transferable belief model, the final detection results are obtained. Real world experiments show the efficacy of the proposed approach in improving the object detection performance, especially in the presence of occlusion.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barzilay, Q., Zelnik-Manor, L., Gutfreund, Y., Wagner, H., Wolf, A.: From biokinematics to a robotic active vision system. Bioinspiration Biomimetics 12(5), 056004 (2017)
Atanasov, N., Sankaran, B., Le Ny, J., Pappas, G.J., Daniilidis, K.: Nonmyopic view planning for active object classification and pose estimation. IEEE Trans. Rob. 30(5), 1078–1090 (2014)
Zhang, G., Kontitsis, M., Filipe, N., Tsiotras, P., Vela, P.A.: Cooperative relative navigation for space rendezvous and proximity operations using controlled active vision. J. Field Robot. 33(2), 205–228 (2016)
Mattamala, M., Villegas, C., Yáñez, J.M., Cano, P., Ruiz-del-Solar, J.: A dynamic and efficient active vision system for humanoid soccer robots. In: Almeida, L., Ji, J., Steinbauer, G., Luke, S. (eds.) RoboCup 2015. LNCS (LNAI), vol. 9513, pp. 316–327. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-29339-4_26
Chen, X., Jia, Y.: Adaptive leader-follower formation control of non-holonomic mobile robots using active vision. IET Control Theory Appl. 9(8), 1302–1311 (2015)
Sanket, N.J., Singh, C.D., Ganguly, K., Fermuller, C., Aloimonos, Y.: GapFlyt: active vision based minimalist structure-less gap detection for quadrotor flight. IEEE Robot. Autom. Lett. 3(4), 2799–2806 (2018)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, San Diego (2005)
CIE 015:2018: Colorimetry. 4th edn., International Commission on Illumination
Kalal, Z., Mikolajczyk, K., Matas, J.: Forward-backward error: Automatic detection and tracking failures. In: International Conference on Pattern Recognition, Istanbul (2010)
Hoseini A., S.P., Nicolescu, M., Nicolescu, M.: Active object detection through dynamic incorporation of Dempster-Shafer fusion for robotic applications. In: International Conference on Vision, Image and Signal Processing (ICVISP), Las Vegas (2018)
Hoseini A., S.P., Nicolescu, M., Nicolescu, M.: Handling ambiguous object recognition situations in a robotic environment via dynamic information fusion. In: IEEE Conference on Cognitive and Computational Aspects of Situation Management, Boston (2018)
Smets, P.: The combination of evidence in the transferable belief model. IEEE Trans. Pattern Anal. Mach. Intell. 12(5), 447–458 (1990)
Smets, P., Kennes, R.: The transferable belief model. Artif. Intell. 66(2), 191–243 (1994)
Denoeux, T.: A neural network classifier based on Dempster-Shafer theory. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 30(2), 131–150 (2000)
Blankenburg, J., et al.: A distributed control architecture for collaborative multi-robot task allocation. In: International Conference on Humanoid Robotics, Birmingham (2017)
Acknowledgment
This work has been supported by Office of Naval Research Award #N00014-16-1-2312.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Hoseini A., S.P., Blankenburg, J., Nicolescu, M., Nicolescu, M., Feil-Seifer, D. (2019). An Active Robotic Vision System with a Pair of Moving and Stationary Cameras. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2019. Lecture Notes in Computer Science(), vol 11845. Springer, Cham. https://doi.org/10.1007/978-3-030-33723-0_15
Download citation
DOI: https://doi.org/10.1007/978-3-030-33723-0_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-33722-3
Online ISBN: 978-3-030-33723-0
eBook Packages: Computer ScienceComputer Science (R0)