Abstract
Existing mobile navigation techniques are not applicable for indoor navigation. Obviously, the best navigator is a human companion. In this paper, we explore to build a wearable virtual navigator for indoor navigation. A novel cognitive vision system is designed which consists of long-term memory and working memory for complicated vision tasks in dynamic environments. The long-term memory mimics the flexibility and scalability of human cognitive memory for domain knowledge representation, and the working memory emulates the routine process and attention selection in human cognitive model for online visual perception. Efficient algorithms for image classification and object detection are organized and performed under cognitive perception framework to achieve real-time performance. Field tests demonstrate its effectiveness and efficiency by recognizing scenes, locations, and landmark objects in real-time, and subsequently providing context-aware assistant to guide the user in the navigation of a complex office environment.
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References
Sanpechuda, T., Kovavisaruch, L.: A Review of RFID Localization: Applications and Techniques. In: Proceedings of ECTI-CON, vol. 2, pp. 769–772 (2008)
Kashiwabara, T., Osawa, H., Shinozawa, K., Imai, M.: TEROOS: A Wearable Avatar to Enhance Joint Activities. In: Proceedings of CHI, pp. 2001–2004 (2012)
Mukawa, M., Lim, J.-H.: A Review of Cognitive Architectures for Visual Memory. In: Proceedings of BICA, pp. 233–238 (2012)
Haverinen, J., Kemppainen, A.: A Geomagnetic Field based Positioning Technique for Underground Mines. In: Proceedings of ROSE, pp. 7–12 (2011)
Filliat, D., Meyer, J.A.: Map-based Navigation in Mobile Robots:-I. A Review of Localization Strategies. Cognitive Systems Research 4, 243–282 (2003)
Meyer, J.A., Filliat, D.: Map-based Navigation in Mobile Robots:-II. A Review of Map-Learning and Path-Planning Strategies. Cognitive Systems Research 4, 283–317 (2003)
Pronobis, A., Caputo, B., Jensfelt, P., Christensen, H.I.: A Realistic Benchmark for Visual Indoor Place Recognition. Robotics and Autonomous Systems 58, 81–96 (2010)
Chong, H.-Q., Tan, A.-H., Ng, G.-W.: Integrated Cognitive Architectures: A Survey. Artif. Intell. Rev. 28, 103–130 (2007)
Bauchhage, C., Wachsmuth, S., Hanheide, M., Wrede, S., Sagerer, G., Heidemann, G., Ritter, H.: The Visual Active Memory Perspective on Integrated Recognition Systems. Image and Vision Computing 26, 5–14 (2008)
Stewart, T.C., Choo, F.-X., Eliasmith, C.: Spaun: A Perception-Cognition-Action Model Using Spiking Neurons. In: Proc. 35th Annual Conference of the Cognitive Science Society, pp. 1018–1023 (2012)
Baddeley, A.: Working Memory: Theories, Models, and Controversies. Annu. Rev. Psychol. 63, 1–29 (2012)
Schneider, W.X.: Visual-Spatial Working Memory, Attention, and Scene Representation: A Neuro-Cognitive Theory. Psychological Research 62, 220–236 (1999)
Li, L., Goh, W., Lim, J.-H., Pan, S.J.: Extended Spectral Regression for Efficient Scene Recognition. Pattern Recognition (submitted)
Dalal, N., Triggs, B.: Histograms of Oriented Gradients for Human Detection. In: Proceedings of CVPR, vol. 1, pp. 886–893 (2005)
Viola, P., Jones, M.: Rapid Object Detection Using a Boosted Cascade of Simple Features. In: Proceedings of CVPR, vol. 1, pp. 511–518 (2001)
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Li, L., Wang, G.S., Goh, W., Lim, JH., Tan, C. (2013). A Wearable Cognitive Vision System for Navigation Assistance in Indoor Environment. In: Lee, M., Hirose, A., Hou, ZG., Kil, R.M. (eds) Neural Information Processing. ICONIP 2013. Lecture Notes in Computer Science, vol 8228. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42051-1_32
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DOI: https://doi.org/10.1007/978-3-642-42051-1_32
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-42050-4
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