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The present paper describes a method for automatic 3D contour model creation for stereo-vision systems. The object model is a triangular surface mesh and a set of aspect models, which consists of model features and model points. Model features and model points are generated using 3D contours, which are estimated by the projected images of the triangular surface mesh from multiple discrete viewing...
Building knowledge for robots can be tedious, especially if focused on object class recognition in home environments where hundreds of everyday-objects - some with a huge intra class variability - can be found. Object recognition and especially object class recognition is a key capability in home-robotics. Achieving deployable results from state-of-the-art algorithms is not yet achievable when the...
We propose a robust and accurate method for multi-target geo-localization from airborne video. The difference between our approach and other approaches in the literature is fourfold: 1) it does not require gimbal control of the camera or any particular path planning control for the UAV; 2) it can instantaneously geolocate multiple targets even if they were not previously observed by the camera; 3)...
This paper presents and examines a hardware implementation of a high speed Iterative Closest Point (ICP) based object tracking system, which uses stereo vision disparities as input. Custom field programmable gate array (FPGA) hardware has been designed to handle the inherent bottlenecks that result from the large input and processing bandwidths of the range data. The custom hardware has been implemented...
Recent development of autostereoscopic displays demands the synthesis of more virtual views in wider baseline, an inevitable trend for future 3DTV systems. However, current standard file formats, e.g. multi-view coding (MVC) and image plus depth, encounter challenging problems to meet the request. Therefore, we propose a new file format, called reduced depth stereo image (RDSI), which saves the color...
This contribution addresses the problem of bias in stereo based motion estimation. Using a biased estimator within a visual-odometry system will cause significant drift on large trajectories. This drift is often minimized by exploiting auxiliary sensors, (semi-)global optimization or loop-closing. In this paper it is shown that bias in the motion estimates can be caused by incorrect modeling of the...
This paper describes an algorithm for creating pseudo stereo image generation (2D-to-3D conversion) and its real-time hardware implementation. The proposed method is developed to fulfill the growing need for high quality generic 3D contents. The algorithm intends to approximate 3D structures of natural scenes and to generate visually pleasing stereo images. The depth data is generated with simple...
In this paper, we propose a deformable-model-driven method to recognize the state of hanging clothes using three-dimensional (3D) observed data. For the task to pick up a specific part of the clothes, it is indispensable to obtain the 3D position and posture of the part. In order to robustly obtain such information from 3D observed data of the clothes, we take a deformable-model-driven approach[4],...
This paper describes a method to localize 3D objects, which is the extension of the segment-based object recognition method to use on a STL CAD model. Models for localization are automatically generated using contour generators, which are estimated by occluding contours of projected images of the CAD model from multiple viewing directions and depth images computed with a graphics accelerator. In addition,...
This paper describes a method to localize objects which are partially buried in an unstructured environment. The objects are limited to surfaces of revolution in the present study. Candidate regions are extracted as convex surface regions from a range data that is obtained by area-based stereo matching. The surface type at each point is determined based on the signs of the maximum and minimum curvatures,...
Many visually-guided robotic systems rely on stereo video data streams to obtain surface models of environmental structure. However stereo video-based 3D point clouds are noisier than those produced from laser-based scanners and are subject to areas of sparse point information corresponding to textureless or specular surfaces. This complicates the process of constructing polygonal meshes from these...
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