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Motion vector estimation of a stereovision camera with inertial sensors

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Języki publikacji
EN
Abstrakty
EN
The aim of the presented work was the development of a tracking algorithm for a stereoscopic camera setup equipped with an additional inertial sensor. The input of the algorithm consists of the image sequence, angular velocity and linear acceleration vectors measured by the inertial sensor. The main assumption of the project was fusion of data streams from both sources to obtain more accurate ego-motion estimation. An electronic module for recording the inertial sensor data was built. Inertial measurements allowed a coarse estimation of the image motion field that has reduced its search range by standard image-based methods. Continuous tracking of the camera motion has been achieved (including moments of image information loss). Results of the presented study are being implemented in a currently developed obstacle avoidance system for visually impaired pedestrians.
Słowa kluczowe
Rocznik
Strony
141--150
Opis fizyczny
Bibliogr. 16 poz., rys., wykr., wzory
Twórcy
autor
Bibliografia
  • [1] Titterton, D.H, Weston J.L. (2004). Strapdown Inertial Navigation Technology. Progress in Astronautics and Aeronautics, MIT Lincoln Laboratory, 2nd. Edition.
  • [2] Ma, Y., Soatto, S., Kosecka, J., Sastry, S. (2003). An Invitation to 3D Vision. Springer.
  • [3] Bruss, A.R., Horn, K.P. (1983). Passive Navigation. Computer Vision, Graphics, and Image Processing 21, 3-20.
  • [4] Argyrost, A.A., Orphanoudakis, S.C. (1997). Independent 3D Motion Detection Based on Depth Elimination in Normal Flow Fields. Comp. Vision and Pat. Recogn. Conf. (CVPR’97), San Juan, Puerto Rico.
  • [5] Skulimowski, P., Strumillo, P. (2008). Refinement of depth from stereo camera ego-motion parameters. Electronics Letters, 44(12), 729-730.
  • [6] Bauer J., Sünderhauf N., Protzel P. (2007). Comparing Several Implementations of Two Recently Published Feature Detector. In Proceedings of the International Conference on Intelligent and Autonomous Systems, IAV, Toulouse, France, 2007.
  • [7] Dante, A., Brookes, M. (2003). Precise real-time outlier removal from motion vector fields for 3D reconstruction. International Conference on Image Processing, I- 393-6, 1.
  • [8] Foxlin, E.M., Harrington, M., Altshuler, Y. (1998). Miniature six-DOF inertial system for tracking HMDs. Proc. SPIE 3362, 214-228.
  • [9] Veth, M., Raquet, J. (2007). Fusion of Low-Cost Imaging and Inertial Sensors for Navigation. NAVIGATION - Journal of the Institute of Navigation, 54(1).
  • [10] Armesto, L., Tornero, J., Vincze, M. (2007). Fast Ego-Motion Estimation with Multi-rate Fusion of Inertial and Vision. The International Journal of Robotics Research, 26(6), 577-589.
  • [11] Jones, E.S., Soatto, S. (2011). Visual-Inertial Navigation, Mapping and Localization: A Scalable Real-Time Causal Approach. International Journal of Robotics Research, 30(4), 407-430.
  • [12] Baranski, P., Polanczyk, M., Strumiłło, P. (2011). Fusion of Data from Inertial Sensors, Raster Maps and GPS for Estimation of Pedestrian Geographic Location in Urban Terrain. Metrology & Measurement Systems, 18(1), 145-158.
  • [13] Pełczyński, P., Ostrowski, B., Rzeszotarski, D. (2009). Mobile System for Passive Navigation in 3D Scene. VIII KKE 2009, East Darłówko, 682-687. (in Polish)
  • [14] Pełczyński, P. (2011). Model Based Estimation of Camera Position in 3D Scene. The 3rd International Conference on Image Processing & Communications, Bydgodszcz.
  • [15] Skulimowski, P., Strumiłło, P. (2007). Obstacle Localization in 3D Scenes from Stereoscopic Sequences. 15th European Signal Processing Conference (EUSIPCO 2007), Poznan, Poland, 2095-2099.
  • [16] Bujacz, M., Skulimowski, P., Strumiłło, P. (2011). Sonification of 3D scenes using personalized spatial audio to aid visually impaired persons. International Conference on Auditory Display, Budapest, Hungary, 2011.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW1-0090-0013
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