Daewoong Kim

An Exhibit Recommendation System Based on Semantic Networks for Museum

Today, information devices as exhibition guide systems to support visitor’s appreciation are introduced in many museums. In this paper, we propose a system for recommending some exhibits suitable for visitor’s interests and requirements with an information device. The proposed system supports a user to appreciate an exhibition and arouses interests of the user by recommending exhibits. Exhibits which the system recommends are selected based on the two types of scores: aggregation scores and influence scores. The aggregation score of an exhibit is defined as the sum of the influence scores of exhibits which have influences on it, and the influence score of an exhibit is defined as the sum of the aggregation scores of exhibits influenced by it. Those scores are calculated based on a semantic network on the exhibits in a museum.

Automatic composition of personalized appreciation route based on semantic relationship between exhibits in museum

Recently, many studies have been reported on ranking and recommendation of a variety of digital contents on the Internet. On the other hand, exhibitions in museums can be considered as actual contents in the real world, so we think that some techniques of ranking and recommendation can be applicable to appreciate exhibitions in a museum effectively and efficiently for a visitor based on his/her interests. Today, information devices as exhibition guide systems to support visitors appreciation are introduced in many museums. In this paper, we propose an approach for composing personalized appreciation route matched to users interest and situation, using the information device. Our system supports a user to appreciate an exhibition well, and arouses users interest by composing a route based on semantic relationship between exhibits.

Convergence Point Adjustment Methods for Minimizing Visual Discomfort Due to a Stereoscopic Camera

The recent rise of the three-dimensional television (3DTV) industry has led to a wide exploitation of the dual-lens stereoscopic camera. However, when the zoom-in function is used, it is possible that a camera object is magnified only with a fixed convergence point, thereby leading to visual discomfort. In this paper, we propose several methods based on which a convergence point can be adjusted to prevent visual discomfort during zoom-in for a dual-lens stereoscopic camera. Further, we produce 3D contents by applying the proposed methods to certain cases and at certain distances and conduct a subjective evaluation. On the subjective evaluation, 48 subjects watch the 3D contents created by the proposed methods and score the stages of the visual comfort. The result of the subjective evaluation shows that some of the proposed methods are more efficient than the others. We hope that these proposed high-efficiency methods can be applied to produce a dual-lens stereoscopic camera that allows convenient stereoscopic photography.

An adjustment method of a convergence point for zoom-in on a dual lens stereoscopic camera

Recently, even non-professional photographers are using a dual lens stereoscopic camera which allows for convenient stereoscopic photography. The necessity for the research comes up, since the dual lens stereoscopic camera can cause visual discomfort during zoom-in due to the fixed convergence point. We propose a method based on which a convergence point can be adjusted to prevent visual discomfort during zoom-in for a dual lens stereoscopic camera. First, the relational model is classified into nine kinds and defined, depending on locations of focus, object, and convergence point. And then, the method to minimize visual discomfort is suggested by adjusting convergence point on the given model.