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Naveen Onkarappa; Angel Sappa |
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Title |
Speed and Texture: An Empirical Study on Optical-Flow Accuracy in ADAS Scenarios |
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2014 |
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IEEE Transactions on Intelligent Transportation Systems |
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TITS |
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15 |
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1 |
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136-147 |
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Abstract |
IF: 3.064
Increasing mobility in everyday life has led to the concern for the safety of automotives and human life. Computer vision has become a valuable tool for developing driver assistance applications that target such a concern. Many such vision-based assisting systems rely on motion estimation, where optical flow has shown its potential. A variational formulation of optical flow that achieves a dense flow field involves a data term and regularization terms. Depending on the image sequence, the regularization has to appropriately be weighted for better accuracy of the flow field. Because a vehicle can be driven in different kinds of environments, roads, and speeds, optical-flow estimation has to be accurately computed in all such scenarios. In this paper, we first present the polar representation of optical flow, which is quite suitable for driving scenarios due to the possibility that it offers to independently update regularization factors in different directional components. Then, we study the influence of vehicle speed and scene texture on optical-flow accuracy. Furthermore, we analyze the relationships of these specific characteristics on a driving scenario (vehicle speed and road texture) with the regularization weights in optical flow for better accuracy. As required by the work in this paper, we have generated several synthetic sequences along with ground-truth flow fields. |
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1524-9050 |
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ADAS; 600.076 |
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Admin @ si @ OnS2014a |
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2386 |
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Arnau Ramisa; David Aldavert; Shrihari Vasudevan; Ricardo Toledo; Ramon Lopez de Mantaras |
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Title |
Evaluation of Three Vision Based Object Perception Methods for a Mobile Robot |
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Journal Article |
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2012 |
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Journal of Intelligent and Robotic Systems |
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JIRC |
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68 |
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2 |
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185-208 |
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This paper addresses visual object perception applied to mobile robotics. Being able to perceive household objects in unstructured environments is a key capability in order to make robots suitable to perform complex tasks in home environments. However, finding a solution for this task is daunting: it requires the ability to handle the variability in image formation in a moving camera with tight time constraints. The paper brings to attention some of the issues with applying three state of the art object recognition and detection methods in a mobile robotics scenario, and proposes methods to deal with windowing/segmentation. Thus, this work aims at evaluating the state-of-the-art in object perception in an attempt to develop a lightweight solution for mobile robotics use/research in typical indoor settings. |
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Springer Netherlands |
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0921-0296 |
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ADAS |
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Admin @ si @ RAV2012 |
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2150 |
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Fernando Barrera; Felipe Lumbreras; Angel Sappa |
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Title |
Multimodal Stereo Vision System: 3D Data Extraction and Algorithm Evaluation |
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2012 |
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IEEE Journal of Selected Topics in Signal Processing |
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J-STSP |
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6 |
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5 |
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437-446 |
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This paper proposes an imaging system for computing sparse depth maps from multispectral images. A special stereo head consisting of an infrared and a color camera defines the proposed multimodal acquisition system. The cameras are rigidly attached so that their image planes are parallel. Details about the calibration and image rectification procedure are provided. Sparse disparity maps are obtained by the combined use of mutual information enriched with gradient information. The proposed approach is evaluated using a Receiver Operating Characteristics curve. Furthermore, a multispectral dataset, color and infrared images, together with their corresponding ground truth disparity maps, is generated and used as a test bed. Experimental results in real outdoor scenarios are provided showing its viability and that the proposed approach is not restricted to a specific domain. |
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1932-4553 |
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ADAS |
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Admin @ si @ BLS2012b |
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2155 |
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Author |
P. Ricaurte ; C. Chilan; Cristhian A. Aguilera-Carrasco; Boris X. Vintimilla; Angel Sappa |
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Title |
Feature Point Descriptors: Infrared and Visible Spectra |
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Year |
2014 |
Publication |
Sensors |
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SENS |
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14 |
Issue |
2 |
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3690-3701 |
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This manuscript evaluates the behavior of classical feature point descriptors when they are used in images from long-wave infrared spectral band and compare them with the results obtained in the visible spectrum. Robustness to changes in rotation, scaling, blur, and additive noise are analyzed using a state of the art framework. Experimental results using a cross-spectral outdoor image data set are presented and conclusions from these experiments are given. |
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ADAS;600.055; 600.076 |
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Admin @ si @ RCA2014a |
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2474 |
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Author |
Mohammad Rouhani; Angel Sappa; E. Boyer |
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Title |
Implicit B-Spline Surface Reconstruction |
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2015 |
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IEEE Transactions on Image Processing |
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TIP |
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24 |
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1 |
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22 - 32 |
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This paper presents a fast and flexible curve, and surface reconstruction technique based on implicit B-spline. This representation does not require any parameterization and it is locally supported. This fact has been exploited in this paper to propose a reconstruction technique through solving a sparse system of equations. This method is further accelerated to reduce the dimension to the active control lattice. Moreover, the surface smoothness and user interaction are allowed for controlling the surface. Finally, a novel weighting technique has been introduced in order to blend small patches and smooth them in the overlapping regions. The whole framework is very fast and efficient and can handle large cloud of points with very low computational cost. The experimental results show the flexibility and accuracy of the proposed algorithm to describe objects with complex topologies. Comparisons with other fitting methods highlight the superiority of the proposed approach in the presence of noise and missing data. |
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1057-7149 |
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ADAS; 600.076 |
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Admin @ si @ RSB2015 |
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2541 |
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