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We have studied ground deformation in the Osaka and Kanto plains, Japan, using ALOS/PALSAR and revealed unique deformations related to active faults. In order to clarify their evolution after 2011, we analyzed strip-map mode images of ALOS-2/PALSAR-2 acquired during 2014–2015. In Osaka, we did not find deformation observed before 2011 such as uplift in southern Kyoto and subsidence along the Arima-Takatsuki...
We propose a novel feature description method called SHORT (Shell Histograms and Occupancy from Radial Transform) for fast 3D object recognition. In 3D object recognition for point cloud data, it is very important to detect keypoints and describe features rapidly because of the huge amount of data involved. The state-of-the-art keypoint detection methods calculate statistics including covariance matrices...
In this paper, we propose a high-speed 3-D object recognition method using new feature values. Features for the object recognition method proposed in this study consist of three values. One is the Difference of Normals (DoN) feature value that has been proposed by Ioannou. The other two represent information about curvature. We use these three-dimensional features to recognize the position and pose...
We propose a reliable 3D position and pose recognition method for complicated scenes including randomly stacked objects. Conventional methods use a small number of features selected by analyzing a target object model for recognition. The small number contributes to high-speed recognition, but actually the features include both "true" and "false" features. True features exist only...
We propose a fast and reliable 3D object detection method that can be applied for complicated scenes consisting of randomly stacked objects. The proposed method uses "3D vector pair" that has a common start point and different end points and it has surface normal distribution as the feature descriptor. By considering the observability of vector pairs, the proposed method has been achieved...
An illumination-invariant background model for detecting objects in dynamic scenes is proposed. It is robust in the cases of sudden illumination fluctuation as well as burst moving background. Unlike previous works, it distinguishes objects from a dynamic background using co-occurrence character between a target pixel and its supporting pixels in the form of multiple pixel pairs. Experiments used...
Piano fingering is one of the important skills for piano performance, especially for beginners. Consequently, technology for recognizing a player's fingering is required in order to develop an automated piano lesson system. The term “piano fingering” refers to which fingers are used for pressing piano keys. In this paper, we propose a method for recognizing piano fingering by analyzing motion of multiple...
In this paper, we propose a method for improving the parametric eigenspace method by automatically removing backgrounds in an input image. The region of a target object is extracted by fitting multiple ellipses to the image and the outer regions around the object are removed as background. The combination of multiple ellipses can flexibly represent various shapes of the target object. In addition,...
We conducted a persistent scatterer interferometry of SAR images acquired by ALOS/PALSAR to reveal ground deformation related to the movement of active faults.
We analyzed TerraSAR-X images and found a good combination of filters and enhancement technique for the automatic landslide detection. We were successfully able to suppress noise in the image, identified landslide signals, and classify landslides from other surface changes. With a parameter set focusing on the completeness of detection, we achieved 98 % of detection from landslide catalog, but we...
We propose a high-speed 3-D object detection method that can recognize the position and pose of objects in complicated scenes consisting of randomly stacked objects. The method's main feature is that a set of distinctive 3-D vector pairs, each of which consists of three different 3-D points, is used for matching objects with an acquired range image. Such distinctive vector pairs represent the local...
In this paper, we proposed a high-speed and robust image matching method for illumination variation. Our method selects a small number of temporally stable pixels. Such pixels realize both high-speed matching and robustness for illumination changing. The previous SCPTM method has an important problem which cannot suppress irregular illumination changes. The reason is that the SCPTM uses some images...
A novel robust model for background subtraction under complex scenes is proposed. Unlike the previous works, it utilizes multiple pixel-pairs which exhibit a stable co-occurrence relation. In training progress, the support pixels are screened by utilizing temporal covariance matrix, and the spatial distributions of support pixels are optimized by spatial sampling based on K-means clustering, in order...
In this study, Robot Motion Performance Platform was developed for the automation of Robot Motion Planning using memory-based techniques. This can be used for robots with various arm and leg forms. The developed Robot Motion Performance Platform is used for the motion performance by name-base to a motion command. In this paper, the realization of motion in a robot with two or more different types...
This paper proposes a method for detecting two or more straight lines from an edge image in a similar way of Hough transform. The method consists of labeling of each edge point to presumed straight lines and RANSAC algorithm to evaluate each label. The Genetic Algorithm (GA), an efficient combinatorial optimization algorithm, is used for the labeling process, and the RANSAC is effective for high accuracy...
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