213 research outputs found

    Uso de las tecnologías de la información y comunicación (tics); para el desarrollo de competencias en el área de educación física en el v ciclo de la EBR

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    El presente trabajo de investigación denominado “el uso de las tecnologías de la información y comunicación (TIC) para el desarrollo de las competencias en el área de educación física en el V ciclo de educación Básica regular” nace de la necesidad dar conocer un poco más sobre el uso de la variable TIC dentro de este campo. Para ello el objetivo general es conocer la importancia del uso de las Tics, para el desarrollo de competencias en el área de educación física en educación primaria. El trabajo académico, es de compilación y el método de investigación es de carácter exploratorio. En la que se ha utilizado como materiales diferentes fuentes bibliográficas, artículos científicos, tesis, etc. Finalmente, se concluye que

    Novel method for vehicle and pedestrian detection based on information fusion

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    A novel approach for vehicle and pedestrian detection based on data fusion techniques is presented. The work fuses information from a 2D laser scanner and a computer camera, to provide detection and classification of vehicles and pedestrians in road environments. Thanks to the data fusion approach, the limitations of each sensor are overcome. Thus reliable system is provided, fulfilling the demands of road safety applications. Classification is performed using each sensor independently. Laser scanner approach is based in pattern matching and vision approach is based in the classical Histogram of Oriented Gradients features approach. A higher stage performs data fusion using Kalman Filter and Global Nearest Neighbors.This work was supported by the Spanish Government through the Cicyt projects (GRANT TRA2010-20225-C03-01) and (GRANT TRA 2011-29454-C03-02). CAM through SEGAUTO-II (S2009/DPI-1509)

    Can low-cost road vehicles positioning systems fulfil accuracy specifications of new ADAS applications?

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    Some new Advanced Driver Assistance Sy stems (ADAS) need on-the-lane vehicle positioning on accurate digital maps, but present applications of vehicle positioning do not justify the surcharge of very ac curate equipment such as DGPS or high-cost inertial systems. For this reason, performance of GPS in autonomous mode is analyzed. Although satisfactory results can be found, in some areas GPS signal is lost or degraded, so it is necessary to know the positioning error when using only inertial system data. A th eoretical approach based on the uncertainty propagation law is used to esti mate the upper limit of distance that can be travelled fulfilling the specifications of an assistance system. Tests results support the conclusions of this approach. Finally, the comb ination of GPS and inertial systems is studied, resulting that the theoretical approach is valid when inertial measurements are used right from the start of GPS signal de gradation, without waiting for a complete loss.The work reported in this paper has been partly funded by the Spanish Ministry of Science and Innovation (SIAC project TRA2007-67786-C02-01 and TRA2007-67786-C02-02) and the CAM project SEGVAUTO.Publicad

    Traffic scene awareness for intelligent vehicles using ConvNets and stereo vision

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    In this paper, we propose an efficient approach to perform recognition and 3D localization of dynamic objects on images from a stereo camera, with the goal of gaining insight into traffic scenes in urban and road environments. We rely on a deep learning framework able to simultaneously identify a broad range of entities, such as vehicles, pedestrians or cyclists, with a frame rate compatible with the strict requirements of onboard automotive applications. Stereo information is later introduced to enrich the knowledge about the objects with geometrical information. The results demonstrate the capabilities of the perception system for a wide variety of situations, thus providing valuable information for a higher-level understanding of the traffic situation

    Pag-Igpaw sa Inip at Inis ng Pagkakapiit: Tulambuhay sa Anyo ng Talinghaga’t Taludturan (Overcoming Ennui and Ire Amidst Incarceration: Narratives in Metaphors and Verses)

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    Kabilang sa itinuturing na “Emergent Literature” sa Pilipinas ang panitikan sa bilangguan. Hindi ito kataka-taka sa bansang may malalim at mahabang kasaysayan ng pagpipiit sa mga tumutunggali sa panlipunang kaayusan, kabilang na ang mga intelektwal, partikular ang mga artista at manunulat. Dahil sa kanilang taglay na progresibo at radikal na katangian, malimit silang maging puntirya ng establisyimento, bukod pa sa kanilang likhang-sining at akdang-pampanitikan, at maging bahagi ng dumadami pang bilang ng mga bilanggong pulitikal sa bansa. Sa loob ng piitan, may pangangailangan na maisadokumento at magawaan ng pag-aaral ang mayaman at masining na karanasan at likha ng mga bilanggong pulitikal na mga artista at manunulat. Kung gayon, layunin ng pag-aaral na ito na suriin ang namayaning damdamin at karanasan ng tatlong makata at manggagawang pangkultura ng pambansa-demokratikong kilusan at dating naging bilanggong pulitikal na sina Kerima Lorena Tariman, Axel Pinpin, at Ericson Acosta. Gamit ang pulitikal na kritisismong pampanitikan, inaasahang mapalitaw sa pag-aaral ng kanilang panulaan sa piitan ang pangkabuuang danas at damdaming namayani sa panahon ng kanilang pagkakapiit. Sa pagtatapos ng pag-aaral, nais patunayan nito na patuloy at buhay hanggang sa kasalukuyan ang makabayang tradisyong pampanitikan sa panulat ng tatlong manggagawang pangkultura at ang mahigpit na ugnayan ng panitikan at lipunan, bukod sa pagpapatingkad at pagbibigay-diin sa kanilang mahigpit na pagkapit sa kanilang prinsipyo at paninindigan. (Prison literature is currently considered as one of the Emergent Literature in the Philippines. This is not new in a society with a deep-seated and long history of putting down dissents in various prison cells who challenged the social order, including groups of intellectuals, especially the ranks of artists and writers. Due to their innate progressive and radical characteristics, they have been one of the main targets of different establishments, as a result of their integration with the masses, whom their artworks and literary works inspired. Unsurprisingly, they contributed to the increasing number of political prisoners in the country. Inside the prison cell, there is a need to document and create a study about the rich and meaningful experiences and works of the political prisoners, emphasizing the significant role of these artists and creative writers. Thus, this study aims to analyze the general emotions and experiences of the three poets and cultural workers of the national democratic movement and former political prisoners, Kerima Lorena Tariman, Axel Pinpin, and Ericson Acosta. Through political literary criticism, this paper will highlight the general emotions and experiences inside the prison by analyzing their prison poetry. Based on the data gathered the results show how optimistic the three poets are amidst the continuous and various attacks from the different establishments. Setbacks and frustrations from their writings through poetry are seen as one of the many reasons that made them feel hopeless, but they still managed to overcome these hindrances by mocking and subverting the state using their pens due to its incompetency, inutile, and anti-people policies. At the end of the study, it supports the argument that the nationalist literary tradition is in a new and fresher breath of writing by these poets-cultural workers. It also shows how strong the connection between literature and society is, aside from the fact that these poets showed unwavering commitment to their principles and advocacies.

    Fast Joint Object Detection and Viewpoint Estimation for Traffic Scene Understanding

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    Environment perception is a critical enabler for automated driving systems since it allows a comprehensive understanding of traffic situations, which is a requirement to ensure safe and reliable operation. Among the different applications, obstacle identification is a primary module of the perception system. We propose a vision-based method built upon a deep convolutional neural network that can reason simultaneously about the location of objects in the image and their orientations on the ground plane. The same set of convolutional layers is used for the different tasks involved, avoiding the repetition of computations over the same image. Experiments on the KITTI dataset show that our efficiency-oriented method achieves state-of-the-art accuracies for object detection and viewpoint estimation, and is particularly suitable for the recognition of traffic situations from on-board vision systems. Code is available at https://github.com/cguindel/Isi-faster-renn

    Discrete features for rapid pedestrian detection in infrared images

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    Proceeding of: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems October 7-12, 2012. Vilamoura, Algarve, Portugal.In this paper the authors propose a pedestrian detection system based on discrete features in infrared images. Unique keypoints are searched for in the images around which a descriptor, based on the histogram of the phase congruency orientation, is extracted. These descriptors are matched with defined regions of the body of a pedestrian. In case of a match, it creates a region of interest in the image, which is classified as a pedestrian / non-pedestrian by an SVM classifier. The pedestrian detection system has been tested in an advanced driver assistance system for urban driving.This work was supported by the Spanish Government through the Cicyt projects FEDORA (GRANT TRA2010-20225-C03- 01) and Driver Distraction Detector System (GRANT TRA2011-29454-C03-02), and by the Comunidad de Madrid through the project SEGVAUTO (S2009/DPI- 1509).Publicad

    Contrast invariant features for human detection in far infrared images

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    Proceeding of: 2012 IEEE Intelligent Vehicles Symposium (IV), Alcalá de Henares, Spain, June 3-7, 2012In this paper a new contrast invariant descriptor for human detection in long-wave infrared images is proposed. It exploits local information histogram of orientations of phase coherence. Contrast in infrared images depends on the temperature of the object and the background, which makes gradient based descriptors less robust, especially in daylight conditions. The objective is to obtain a scale, brightness and contrast invariant descriptor that can successfully detect pedestrians in images taken with a cheap, temperature-sensitive, uncooled microbolometer. The descriptor, packed into grids is feed to a Support Vector Machine classifier. The algorithm has been tested in night and day sequences and its performance is compared with a day only descriptor: the histogram of oriented features (HOG).This work was supported by the Spanish Government through the Cicyt projects FEDORA (GRANT TRA2010- 20225-C03-01) and VIDAS-Driver (GRANT TRA2010- 21371-C03-02), and the Comunidad de Madrid through the project SEGVAUTO (S2009/DPI-1509).Publicad

    Detección y localización de obstáculos mediante U-V Disparity con CUDA

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    Tradicionalmente la detección de obstáculos es un tema de investigación de gran interés en visión por computador aplicada tanto a la navegación de robots, como a los sistemas avanzados de ayuda a la conducción (ADAS). Aunque otras tecnologías como por ejemplo el láser, presentan buenos resultados para detectar obstáculos en entornos urbanos, la visión por computador proporciona información 2D &- ó 3D con visión estéreo &- que mejora la interpretación del entorno en exteriores. En este artículo se presenta una implementación en tiempo real de la construcción del mapa denso de disparidad y del U-V disparity, que son utilizados para la detección y localización de obstáculos. Para minimizar los efectos sobre el tiempo de cómputo que ocasionan tanto la construcción del mapa denso de disparidad, como la del U-V disparity, se han implementado ambos mediante el uso de GPUs (Unidades de Procesamiento Gráfico) por su alto rendimiento con algoritmos paralelizables.Publicad
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