Masaaki Iiyama

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Recognizing structure of human body is important for modeling human motion. Human body is usually represented as an articulate model, which consists of the rigid parts and the joint points between them. The structure of the human body is specified by the joint points. In this paper we propose a novel method for estimating the location of joint points from(More)
We propose a method for acquiring a 3D shape of human body segments accurately. Using a light stripe triangulation range finder, we can acquire accurate the 3D shape of a motionless object in a dozen of seconds. If the object were to move during the scanning, the acquired shape would be distorted. Naturally, humans move slightly for making balance while(More)
In this paper, we present a novel approach for extracting silhouettes by using a particular pattern that we call the random pattern. The volume intersection method reconstructs the shapes of 3D objects from their silhouettes obtained with multiple cameras. With the method, if some parts of the silhouettes are missed, the corresponding parts of the(More)
In this paper, we propose a novel method for reconstructing the shape model of a non-rigid object. We represent the non-rigid object as the union of rigid components, and acquire range images of the object and motion of each component while the object varies its shape. We acquire the range images using one-shot scanning, and we use marker-based motion(More)
In this paper, we propose a method to measure specular objects regardless occlusion. The main contribution of this paper is that we have shown that the scattering of incident and specular reflection enable us to measure occluded surfaces. We locate objects in a tank filled with participating media, irradiate a laser beam to the objects, and observe the(More)
—This paper presents an artifact-free super-resolution texture mapping from multiple-view images. The multiple-view images are upscaled with a learning-based super-resolution technique and are mapped onto a 3D mesh model. However, mapping multiple-view images onto a 3D model is not an easy task, because artifacts may appear when different upscaled images(More)
Photometric stereo is a method of recovering surface normals (needle map) from images. The surface integral of surface normals is used to reconstruct a depth map; however, the depth edges, which are discontinuous boundaries of the depth map, pose a problem for pho-tometric stereo. When the surface of objects includes depth edges, the reconstructed depth map(More)
A new approach for reconstructing the arbitrary views of an object is proposed. The images are grabbed by the multiple camera system. The corresponding pairs among the images are determined from the relation of the camera positions. The exact depth measurement of each pixel of an object has been determined from the multiple image pairs. The synthesized(More)
—Most vision-based 3D acquisition methods including both passive and active methods have a limitation in that cameras must be able to observe the surface to be measured. If this is not possible, that is to say, if the surface is occluded, most of the methods cannot acquire the surface shape. In this paper, we present a method that can acquire the 3D points(More)