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There have been many implementations of virtual reality, using audio and visual senses. However, implementations of mixed reality (MR) have thus far only dealt with the visual sense. We have developed an MR system that merges real and virtual worlds in both the audio and visual senses, wherein the geometric consistency of the audio sense was fully(More)
This paper proposes a method to detect and identify multiple objects in an image using grid voting of object center positions estimated from local descriptor keypoint matches. For each keypoint match, the proposed method estimates the object center position using scale and orientation associated with the keypoints. Then, it casts a vote for an image grid(More)
In this paper, we propose a Scale and Rotation Invariant Implicit Shape Model (SRIISM), and develop a local feature matching based system using the model to accurately locate and identify large numbers of object instances in an image. Due to repeated instances and cluttered background, conventional methods for multiple object instance identification suffer(More)
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