1,721,172 research outputs found
Crecimiento, empleo y demografía en el Caribe colombiano, 1973-1994
No full textRosado Salgado, Luis Arturo-1ec11434-0983-4ac7-8b70-e6987955c358-
Hotel Ejecutivo Four Seasons Corregidora, Querétaro
No full textTesis (Ingeniero Arquitecto), Instituto Politécnico Nacional, Licenciatura, Escuela Superior de Ingeniería y Arquitectura, Unidad Tecamachalco, 2017, 1 archivo PDF, (279 páginas). tesis.ipn.m
Efficient Spatio-Temporal Hole Filling Strategy for Kinect Depth Maps
No full textIn this paper we present an efficient hole filling strategy that improves the quality of the depth maps obtained with the Microsoft Kinect device. The proposed approach is based on a joint-bilateral filtering framework that includes spatial and temporal information. The missing depth values are obtained applying iteratively a joint-bilateral filter to their neighbor pixels. The filter weights are selected considering three different factors: visual data, depth information and a temporal-consistency map. Video and depth data are combined to improve depth map quality in presence of edges and homogeneous regions. Finally, the temporal-consistency map is generated in order to track the reliability of the depth measurements near the hole regions. The obtained depth values are included iteratively in the filtering process of the successive frames and the accuracy of the hole regions depth values increases while new samples are acquired and filtered
Adaptive background modeling in multicamera system for real-time object detection
No full textWe present an adaptive and efficient background modeling strategy for real-time object detection in multicamera systems. The proposed approach is an innovative multiparameter adaptation strategy of the mixture of Gaussian (MoG) background modeling algorithm. This approach is able to efficiently adjust the computational requirements of the tasks to the available processing power and to the activity of the scene. The innovative approach allows one to adapt the MoG without a significant loss in the detection accuracy while contemporarily adhering to the real-time constraints. The adaptation strategy works at the local level by modifying, independently, the MoG parameters of each task, and then, whenever the results of the local strategy are not satisfactory, a global adaptation strategy starts that aims at balancing the workload among the tasks. Our approach has been tested on three different data sets, including several image sizes, heterogeneous environments (indoor and outdoor scenarios), and different real-time constraints. The results show that the proposed adaptive system is well suited for multicamera applications thanks to this efficiency and adaptability; it guarantees real-time highly accurate detections
Adaptive spatio-temporal filter for low-cost camera depth maps
No full textIn this paper we present an adaptive spatio-temporal filter that aims to improve low-cost depth camera accuracy and stability over time. The proposed system is composed by three blocks that are used to build a reliable depth map of static scenes. An adaptive joint-bilateral filter is used to obtain consistent depth maps by jointly considering depth and video information and by adapting its parameters to different levels of estimated noise. Kalman filters are used to reduce the temporal random fluctuations of the measurements. Finally an interpolation algorithm is used to obtain consistent depth maps in the regions where the depth information is not available. Results show that this approach allows to considerably improve the depth maps quality by considering spatio-temporal information and by adapting its parameters to different levels of noise
Background foreground segmentation with RGB-D Kinect data: An efficient combination of classifiers
No full textScalable software architecture for on-line multi-camera video processing
No full textIn this paper we present a scalable software architecture for on-line multi-camera video processing, that guarantees a good trade off between computational power, scalability and flexibility. The software system is modular and its main blocks are the Processing Units (PUs), and the Central Unit. The Central Unit works as a supervisor of the running PUs and each PU manages the acquisition phase and the processing phase. Furthermore, an approach to easily parallelize the desired processing application has been presented. In this paper, as case study, we apply the proposed software architecture to a multi-camera system in order to efficiently manage multiple 2D object detection modules in a real-time scenario. System performance has been evaluated under different load conditions such as number of cameras and image sizes. The results show that the software architecture scales well with the number of camera and can easily works with different image formats respecting the real time constraints. Moreover, the parallelization approach can be used in order to speed up the processing tasks with a low level of overhead
De Colombia al norte santafesino: práctica profesional en INTA Reconquista
No full textDurante los meses de agosto y diciembre de 2024, se realizó una práctica internacional en la
Estación Experimental Agropecuaria (EEA) del INTA Reconquista y la Universidad Nacional del
Nordeste (UNNE), cuyo eje fue evaluar un híbrido de papaya bajo frío, complementada con acti vidades en áreas multidisciplinarias. Durante la experiencia se integró teoría y práctica, forta leciendo habilidades académicas, profesionales e interpersonales, contribuyendo significativa me a la formación integral del estudiante como futuro ingeniero agrónomo.EEA ReconquistaFil: Forero Salgado, Luis Miguel. Universidad de Tolima; ColombiaFil: Ybran, Romina Gisela. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Reconquista; Argentin
Accurate depth-color scene modeling for 3D contents generation with low cost depth cameras
No full textIn this paper, we present a depth-color scene modeling strategy for indoors 3D contents generation. It combines depth and visual information provided by a low-cost active depth camera to improve the accuracy of the acquired depth maps considering the different dynamic nature of the scene elements. Accurate depth and color models of the scene background are iteratively built, and used to detect moving elements in the scene. The acquired depth data is continuously processed with an innovative joint-bilateral filter that efficiently combines depth and visual information thanks to the analysis of an edge-uncertainty map and the detected foreground regions. The main advantages of the proposed approach are: removing depth maps spatial noise and temporal random fluctuations; refining depth data at object boundaries, generating iteratively a robust depth and color background model and an accurate moving object silhouette
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