Real-time micro-environmental observation with virtual reality

In this paper, the observation technique on the micro environments with a real-time virtual reality camera system, which is constructed with a dynamic focusing lens and a smart vision sensor using the "depth from focus" criteria, is discussed. However, one drawback opt the all-in-focus image is that there is no information about the depth of objects. Then, it is also important to reconstruct a micro 3D environment in real-time to actuate objects in the micro virtual environments. Important factors to realize real-time system with the "depth from focus" criteria, which can obtain the all in-focus image and micro 3D reconstruction, simultaneously, are discussed. Finally, the real-time system is constructed by a dynamic focusing lens, which can change the focus in high frequency, and a smart vision system which is capable in capturing and processing the image data in high speed with SIMD architecture.

[1]  Nobuyuki Ohya,et al.  A new, compact and quick-response dynamic focusing lens , 1997, Proceedings of International Solid State Sensors and Actuators Conference (Transducers '97).

[2]  Kiyoharu Aizawa,et al.  Acquisition of an all-focused image by the use of multiple differently focused images , 1998, Systems and Computers in Japan.

[3]  Shree K. Nayar,et al.  Real-time focus range sensor , 1995, Proceedings of IEEE International Conference on Computer Vision.

[4]  Daniel Raviv,et al.  Novel active-vision-based visual-threat-cue for autonomous navigation tasks , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  Shree K. Nayar,et al.  Minimal operator set for passive depth from defocus , 1996, Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Shree K. Nayar,et al.  Shape from Focus , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Takeo Kanade,et al.  Sensory Attention: Computational Sensor Paradigm for Low-Latency Adaptive Vision , 1997 .