Kunio Osada

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In this paper, we describe a shape-based 3D model retrieval method based on multi-scale local visual features. The features are extracted from 2D range images of the model viewed from uniformly sampled locations on a view sphere. The method is appearance-based, and accepts all the models that can be rendered as a range image. For each range image, a set of(More)
In this paper, we describe a method of shape-based 3D model retrieval that employs a set of 3D, local, multi-scale features extracted from a voxel representation of a 3D model to be compared. The method first convert a surface based 3D model into a voxel model. Then, a novel 3D extension of the popular 2D image feature, the Scale Invariant Feature Transform(More)
A local shape feature has an advantage in dealing with deformable or articulated 3D models. We evaluate the performance of our local, 2D visual features and their integration method based of the bag-of-features approach on the SHREC'08 CAD Model Track task. The evaluation showed that, it performed very well, winning the 2 nd place in the contest, although(More)
Text detection in images of natural scenes is important for scene understanding, content-based image analysis, assistive navigation and automatic geocoding. Achieving such text detection is challenging due to complex backgrounds, non-uniform illumination, and variations in text font, size, and orientation. In this paper, we present a novel hybrid approach(More)
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