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In this paper, the problem of retrieving the three-dimensional reconstruction of the ground scene observed by a Synthetic Aperture Radar System is addressed. To obtain such result, Multi-Pass systems are considered jointly with two recently proposed estimation techniques: the Compressive Sensing and the SAR Statistical Tomography.
Geometrical features are widely used in the SAR ship recognition. Two-dimensional (2D) features are sometimes ambiguous and the three-dimensional (3D) ones are hence preferred. Most of the existing researches are based on the 3D coordinate estimation of the scattering centers. These techniques may lose efficiency when working with ocean ships, due to their complicated motion on the waves and the scattering...
On the 12th of January 2010, Haiti was struck by a M7.0 earthquake; the hypocenter (18.443°N, 72.571°W, Depth 13 km) was located very close to the capital Port-au-Prince, causing considerable damage to buildings and infrastructure in the city and its conurbation and a high number of human fatalities. For evaluation of the co-seismic surface shift caused by this earthquake, especially at the Enriquillo-Plantain...
The interest for advanced methods of full 3D SAR imaging of volumetric forest scatterers is rapidly increasing. In particular, multibaseline SAR tomographic elevation beamforming i.e. spatial spectral estimation is a promising technique. Recently, this concept has been integrated with the differential interferometry concept, producing the new differential tomography mode which yields ‘space-time’...
The typical local stereo matching for disparity estimation can deliver accurate disparity maps by a well-designed cost aggregation method, but usually suffers from natively high computational complexity due to its dense processing. To address it, we propose a fast algorithm with search point reduction on spatial and disparity domains to generate a sparse search map. The sparse search map guides the...
In this paper, a human detection and tracking system in a crowded environment is presented. The biggest challenge of the system is to detect occluded people from the captured video where visible information of the occluded people in a camera is reduced. Many researchers proposed to reconstruct the occluded information from other cameras which are installed in the same place with different viewing...
In this paper, we present a real time biologically motivated 3D motion classifier cells integrating the depth information generated from a stereo input implemented in an active vision system. The proposed approach is accurately able to detect and estimate multiple interfered 3D complex motions under the absence of predefined spatial coherence. Moreover, the system has ability to examine the response...
We evaluate the robustness of five regression techniques for monocular 3D pose estimation. While most of the discriminative pose estimation methods focus on overcoming the fundamental problem of insufficient training data, we are interested in characterizing performance improvement for increasingly large training sets. Commercially available rendering software allows us to efficiently generate large...
This paper presents a model-based hierarchical particle filtering algorithm to estimate the pose and anthropometric parameters of humans in multi-view environments. Our method incorporates a novel likelihood measurement approach consisting of an approximate partitioning of observations. Provided that a partitioning of the human body model has been defined and associates body parts to state space variables,...
Dead-reckoning navigation in the deep sea is subject to errors due to accumulation of sensor inaccuracies. As no global referencing method exists for the deep sea like, e.g., GNSS (global navigation satellite system) for land or airborne vehicles other referencing solutions need to be employed. SLAM (Simultaneous Localization And Mapping) is a technique that exploits significant environmental features...
Eye tracking devices have been extensively used to study human selection mechanisms and promoted the development of computational models of visual attention, whose well known outcomes are the saliency maps. Among the eye trackers, wearable ones have the advantages of allowing the estimation of the Point of Regard (POR) while performing natural tasks, instead of experimental, static lab settings. The...
Firstly, this paper analyzes the shortages of current Urban Landuse Evaluation of the comprehensive planning. Secondly, this paper establishes the standards of Urban Landuse Evaluation in Nanjing on the base of state standards which will come to use. Thirdly, this paper establishes four types of land: unbuildable landuse, unsuitable build landuse, buildable landuse and suitable build landuse, through...
In this paper, a new method is presented for three dimensional (3D) localization of narrow band acoustic sources in shallow ocean with non-Gaussian noise. The noise is modeled as a Gaussian mixture with a small number of components. The new algorithm consists of an initialization step to obtain rough estimates of the unknown parameters followed by an update step in which the initial estimates are...
Estimating the location of mobile terminals in dense urban environments is still an open issue. This paper proposes a new radiolocation technique which is robust to severe Non-Line-of-Sight and multipath propagation conditions that are typical of urban microcellular and picocellular systems. In the proposed technique, three-dimensional location estimation can be achieved by counting the number of...
Given a pair of images, a stereoscopic display should execute the image plane calibration, the depth map estimation, and the multiple views rendering to show a 3-D picture. Among all signal processing stages, the depth estimation is the most critical one. This paper presents a real-time depth map estimation algorithm as well as parallel software architecture based on a GPU processor. The experimental...
Semantic visual perception for knowledge acquisition plays an important role in human cognition, as well as in the learning process of any cognitive robot. In this paper, we present a visual information abstraction mechanism designed for continuously learning robotic systems. We generate spatial information in the scene by considering plane estimation and stereo line detection coherently within a...
Successful recognition and pose estimation of logs and trees as well as workspace modeling in the forest environment is essential for extensive automation of the harvesting and logging tasks of forestry machines. However, the freeform features of logs, few reliable textural features, large edge extraction errors, and segmentation faults caused by the barks on the surface of the logs present clear...
We present a novel plane extraction algorithm based on coplanar line pairs for poorly textured scenes. Coplanar line pairs are extracted from intersecting line pairs and matched between two views, and their correspondences act as geometric primitives for 3D planar patch extraction. Each correspondence generates a plane hypothesis by estimating planar homography using the compatibility constraint with...
Pose estimation is an important capability for mobile agents. A wide variety of solutions have been proposed, but work in the literature has focused primarily on solutions for robots whose mobility is restricted to the ground plane. In this work we present a framework for 6DOF pose estimation. Normally the increased computational cost associated with this higher dimensional space makes pose estimation...
This article proposes a novel solution to the Pose Estimation problem for Ego-Motion from stereo camera images. The approach uses a nonlinear function, derived from the concept of Gibbs' Entropy, which is robust by nature to the presence of noise and outliers in the visual features. The SIFT algorithm is used to collect and match the features from stereo images. The 3-vectors quaternion parameterization...
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