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In this present work, we propose to define a novel surface registration approach using the generalized Hausdorff distance in the shape space. It is based on the selection of local and invariant points under the transformations of the 3D motion group. These points are selected from two level sets extracted from geodesic local coordinates with respect to a given reference. The optimal number of invariant...
In this paper, we present on the research of semantic-based 3D model retrieval system and its developed framework. We use RDF annotation to label 3D models for improving retrieval precision. The framework contains three parts: preprocessing, feature extraction and similarity measurement. The parts are recommended to analyze the 3D model. In the preprocessing part, we deploy PCA to make models normalization...
The selection and manipulation of 3D content in desktop virtual environments is commonly achieved with 2D mouse cursor-based interaction. However, by interacting with image-based techniques we introduce a conflict between the 2D space in which the 2D cursor lays and the 3D content. For example, the 2D mouse cursor does not provide any information about the depth of the selected objects. In this situation,...
We present a system for free-form surface modeling and editing that allows a user to create a surface and modify a shape by shaded image using stroke-based drawing tools. After user input sketch contours, smooth distance fields are computed, then translated into height fields. A closed smooth surface is created by the contours and the inferred height fields. Further, user can editing surface by sketched...
Selection of multiple objects is a frequent interaction task in virtual environments. Accomplishing this task efficiently and intuitively is difficult, especially in cases where there are a very large number of objects to be selected. In this work, we seek to investigate two well-known techniques, a spherical brush and a box-shaped lasso for multiple object selection (MOS), and compare them to a new...
This paper proposes an approach to create appropriate virtual 3-D scenes to be shared with many people on a novel glasses-free table-top 3-D display. For maintaining appropriate omni-directional observation, the virtual objects must be situated in a certain volume. We first analyze and parameterize the volume derived from the geometrical configurations of the 3-D display. Then we simplify the volume...
A novel learning based framework for efficient heterogeneous faces synthesis is proposed. Based on the same spectral distribution of each modality, a statistical probability model is developed for the mapping learning problem between two groups of facial appearances, instead of the traditional linear regression model. Furthermore, in order to eliminate the influences of facial structure and spectrum...
This paper proposes an efficient technique to detect ear from 3D profile face range images and is invariant to rotation and scale. It makes use of graph connected components constructed using the edges of the depth map image of the range data for ear detection. It can detect left and right ears at the same time without imposing any additional cost or specific training. The technique has been tested...
Sensor deployment is a fundamental issue in a wireless sensor network, which often dictates the overall network performance. Previous studies on sensor deployment mainly focused on sensor networks on 2D plane or in 3D volume. In this paper, we tackle the problem of optimal sensor deployment on 3D surfaces, aiming to achieve the highest overall sensing quality. In general, the reading of a sensor node...
In reconstructing 3-D shape from images based on feature points, we usually define a triangular mesh that has those feature points as vertices, and display the object as a polyhedron. If the object itself is a polyhedron, however, some of the displayed edges may be inconsistent with the true shape. For this problem, Nakatsuji et al. proposed a method that automatically eliminates such inconsistencies...
In this paper we propose a novel segmentation method that integrates prior shape knowledge obtained from a 3D statistical model into the Markov Random Field (MRF) segmentation framework to deal with severe artifacts, noise and shape deformations. The statistical model is learned using a Probabilistic Principal Component Analysis (PPCA), which allows us to reconstruct the optimal shape and to compute...
We introduce a framework for analyzing symmetry of 3D anatomical structures using elastic deformations of their boundaries (surfaces). The basic idea is to define a space of parameterized surfaces and to compute geodesic paths between the objects and their arbitrary reflections using a Riemannian structure. Elastic matching, based on optimal (non-linear) re-parameterizations (grid deformations) of...
This paper presents new fuzzy based feature matching technique for 3D reconstruction from multiple views. Three fuzzy inputs are developed based on 1) traditional feature matching, 2) normalized RGB histogram, and 3) orientation similarity of the neighboring points. Fuzzy output represents a level of feature matching. The proposed technique is compared with the traditional correlation measure. Three...
Crowd-sourcing tools such as Mechanical Turk are popular for annotation of large scale image data sets. Typically, these annotations consist of bounding boxes or coarse outlines of objects, in order to keep the interface as simple as possible and to respect browser constraints. However, as most browsers now contain functionality to quickly process images and render shapes to the browser through JavaScript,...
Image segmentation and non-rigid registration are two widely investigated tasks in medical image analysis. Concurrent segmentation and registration methods have received considerable attention in recent years. While some models have been shown to give interesting results, most of them are either able to improve segmentation results alone or able to correct rigid rotation and translation only. In addition,...
This paper describes a three dimensional SOKUIKI sensor module with a roundly swinging mechanism for providing three dimensional coordinate data and the corresponding light-receiving intensity data on a laser reflecting point. This sensor module scans wide viewing scanning area around itself in high speed. The auther's group had already developed and reported on the three dimensional SOKUIKI sensor...
We develop the framework of decentralised Navigation Functions for the case of multiple agents of arbitrary shapes and sensing areas around them moving in N-dimensional space. Unlike previous approaches utilising the Navigation Functions methodology, the construction here does not rely on diffeomorphisms, thus reducing the computational cost of the algorithm. The resulting potential field is absolutely...
This work addresses the problem of real-time 3D shape based object class recognition, its scaling to many categories and the reliable perception of categories. A novel shape descriptor for partial point clouds based on shape functions is presented, capable of training on synthetic data and classifying objects from a depth sensor in a single partial view in a fast and robust manner. The classification...
This paper describes methods of environment map representation and plane detection for daily assistive robots. Under the assumption that 3D information of around environment is constructed by collecting range data gradually measured, we propose an effective map representation named TCCM (Time-series Composite Cuboid Map). The method copes with temporal sequence explicitly, and map updating is efficiently...
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