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VOLUME 7 , ISSUE 5 (December 2014) > List of articles
Special issue ICST 2014
Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 7, Issue 5, Pages 1-4, DOI: https://doi.org/10.21307/ijssis-2019-123
License : (CC BY-NC-ND 4.0)
Published Online: 15-February-2020
The authors are developing a simulation-based environmental learning support system using Kinect sensors. Obviously, it is impossible for learners to experience the actual paleontological environment, and it is therefore difficult for them to learn about the environments and lives. Then, we proposed an immersive animation display system using Kinect sensors and their human skeleton-tracking function. The system animates paleontological animals and their environment on the screen and displays information of the animals in synchronization with learners’ action. Learners are measured their location and action in real time, and then the animation is controlled based on information output from sensors. In this way, the system provides learners with a real body experience and sense of immersion that they have entered the paleontological environment. In order to evaluate the system, we conduct an experiment using the system, and interview the participants about the sense of immersion into environment in the system. The experimental results confirm that most learners feel a tangible improvement in the sense of immersion due to the enjoyment of moving their body and acquisition of body experience.
 Akiko Deguchi, Shigenori Inagaki, Fusako Kusunoki, Etsuji Yamaguchi, Yoshiaki Takeda, Masanori Sugimoto, 2010, “Vegetation interaction game: Digital SUGOROKU of vegetation succession for children,” ICEC2010, pages 493-495.
 Takayuki Adachi, Masafumi Goseki, Keita Muratsu, Hiroshi Mizoguchi, Miki Namatame, Masanori Sugimoto, Fusako Kusunoki, Etsuji Yamaguchi, Shigenori Imagaki, Yoshiaki Takeda, 2013, “Human SUGOROKU: Full-body Interaction System for Students to Learn Vegetation Succession,” IDC2013, pages 364-367.
 Jamie Shotton, Andrew Fitzgibbon, Mat Cook, Toby Sharp, Mark Finocchio, Richard Moore, Alex Kipman, and Andrew Blake, 2011,“ Real-Time Human Pose Recognition in Parts from a Single Depth Image”, 2011 IEEE Int. Conf. CVPR, pages 1297-1304.