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Author: search.filters.author.Chotikakamthorn, NoppornSubject: search.filters.subject.Virtual reality

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    A light-pointing method for virtual object selection and manipulation in a monoscopic viewing system
    (2005-12-01)
    Kanjanasupark, Pornchai
    ;
    Chotikakamthorn, Nopporn
    Virtual object selection and re-location are two basic object manipulations that can be found in most VR/VE applications. Many interaction metaphors have been developed for object manipulation in VR/VE environments. Of particular interest is the ray-casting method. The method applies a light ray metaphor in selecting and moving a virtual object. However, the method implicitly requires a stereoscopic viewing system to be efficiently use. With a monoscopic viewing system, inefficiency of the method in terms of task completion time is demonstrated in this paper. For a system using a monoscopic viewing device, a light-pointing method based on a laser-pointer metaphor is proposed to alleviate the shortcoming of the original ray-casting method. Compared with the ray-casting method, it was found from the experiment that the proposed method is noticeably more efficient in terms of task completion time. © 2005 IEEE.
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    Location invariant features for relative hand position classification
    (2004-12-27)
    Eungprasert, Surawej
    ;
    Chotikakamthorn, Nopporn
    Hand posture recognition is applied in various research areas such as an automated sign language translation system, and manual-based human-computer interface. One of the problems found in magnetic tracker-based hand posture recognition is caused by change of user body location while using the system. In this paper, by using orientation measures obtained from the 6-DOF location sensing device, a hand posture feature which is invariant to change in a user's absolute body location is derived. This invariance property is achieved by exploiting the constraints imposed by human arm kinematics, as well as by the feasible and typical range of hand postures allowed by most sign languages. Results from the experiment with real measurements are included.
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    Location invariant features for relative hand position classification
    (2004-11-17)
    Eungprasert, Surawej
    ;
    Chotikakamthorn, Nopporn
    Hand posture recognition is applied in various research areas such as an automated sign language translation system, and manual-based human-computer interface. One of the problems found in magnetic tracker-based hand posture recognition is caused by change of user body location while using the system. In this paper. by using orientation measures obtained from the 6-DOF location sensing device, a hand posture feature which is invariant to change in a users absolute body location is derived. This invariance property is achieved by exploiting the constraints imposed by human arm kinematics, as well as by the feasible and typical range of hand postures allowed by most sign languages. Results from the experiment with real measurements are included.