17 research outputs found

    Multigranularity Representations for Human Inter-Actions: Pose, Motion and Intention

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    Tracking people and their body pose in videos is a central problem in computer vision. Standard tracking representations reason about temporal coherence of detected people and body parts. They have difficulty tracking targets under partial occlusions or rare body poses, where detectors often fail, since the number of training examples is often too small to deal with the exponential variability of such configurations. We propose tracking representations that track and segment people and their body pose in videos by exploiting information at multiple detection and segmentation granularities when available, whole body, parts or point trajectories. Detections and motion estimates provide contradictory information in case of false alarm detections or leaking motion affinities. We consolidate contradictory information via graph steering, an algorithm for simultaneous detection and co-clustering in a two-granularity graph of motion trajectories and detections, that corrects motion leakage between correctly detected objects, while being robust to false alarms or spatially inaccurate detections. We first present a motion segmentation framework that exploits long range motion of point trajectories and large spatial support of image regions. We show resulting video segments adapt to targets under partial occlusions and deformations. Second, we augment motion-based representations with object detection for dealing with motion leakage. We demonstrate how to combine dense optical flow trajectory affinities with repulsions from confident detections to reach a global consensus of detection and tracking in crowded scenes. Third, we study human motion and pose estimation. We segment hard to detect, fast moving body limbs from their surrounding clutter and match them against pose exemplars to detect body pose under fast motion. We employ on-the-fly human body kinematics to improve tracking of body joints under wide deformations. We use motion segmentability of body parts for re-ranking a set of body joint candidate trajectories and jointly infer multi-frame body pose and video segmentation. We show empirically that such multi-granularity tracking representation is worthwhile, obtaining significantly more accurate multi-object tracking and detailed body pose estimation in popular datasets

    Detección de personas en presencia de grupos

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    La visión por computador es una rama de la informática, donde se trata de dotar a las máquinas de ese estimable sentido que es la vista. Esto unido a la inteligencia artificial, donde se quiere conseguir que un computador tenga consciencia, puede lograr que de manera automática y autónoma un ordenador pueda, por ejemplo, vigilar la seguridad de las personas. Por otro lado, la vídeo-vigilancia puede procesar diferentes tipos de entradas para generar alertas que un usuario pueda utilizar para evitar un insatisfactorio suceso. No hace falta decir que la vídeo-vigilancia no es nada sin la visión artificial, la cual es la encargada de hacer todo el procesamiento de las entradas que proporcionan las cámaras, y dar esas salidas que son las detecciones deseadas. Este proyecto consta de, por lo tanto, una unión de ambas. Debe de conseguir, utilizando diferentes herramientas, la transparente unificación de todos estos conceptos. Para ello, se quiere como objetivo final conseguir detectar personas de una manera eficaz cuando estas están en grupos de mayor o menor dimensión. Concretando, buscamos una mejora en la detección de personas en presencia de grupos. En este tipo de escenarios es aún más compleja la detección, dado que las personas pueden están altamente ocluidas unas con otras. Este proyecto lo podríamos catalogar como I+D+i. Dado que se investiga todo lo relacionado con la visión artificial y la vídeo-vigilancia. Se desarrolla un software a modo de prototipo que dispone de todas las funcionalidades deseadas. Y también se innova en la implementación propia de diferentes algoritmos. Por último, es importante recalcar que la principal vocación del presente trabajo es sentar las bases para el desarrollo posterior de diferentes aplicaciones relacionadas con la monitorización automática de escenas tanto desde el punto de vista de la implementación eficiente como desde el punto de vista del diseño de nuevos algoritmos de detección.Computer vision is a field in computer science, which tries to provide machines with that appreciable sense that is sight. This coupled with artificial intelligence, where you want a computer to have consciousness, can make automatically and autonomously that computers, for example, monitor people safety. Furthermore, video surveillance can process different types of inputs to generate alerts that a user can use to avoid an unsatisfactory event. Needless to say that video surveillance is nothing without the artificial vision, which is responsible for all of the processing of the inputs, which the cameras provide, and give those outputs, which are the desire detections. This project involves, therefore, a junction of the two issues. It must achieve, using different tools, the transparent unification of all these concepts. Therefore, our final aim is to detect people effectively in crowd scenes. Specifying, we search an improvement in the people detection in the presence of the groups. In this type of scenario is even more complex detection, since people can are highly occluded with other persons. This project could be included as a I+D+i type. Since everything related to computer vision and video surveillance is investigated. Specific software is developed as a prototype that has all the desired features. And also innovates in the actual implementation of different algorithms. Finally, make clear that what we want is to be helpful to different projects that linked to this one, can increase knowledge, effectiveness and efficiency of different investigations and future implementations. Finally, it is important to stress that the main vocation of the present work is to as much lay the foundations for the later development of different applications related to the automatic monitoring from scenes from the point of view of the efficient implementation as from the point of view of the design of new algorithms of detection

    Combining background subtraction and temporal persistency in pedestrian detection from static videos

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    Selected Papers from the First International Symposium on Future ICT (Future-ICT 2019) in Conjunction with 4th International Symposium on Mobile Internet Security (MobiSec 2019)

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    The International Symposium on Future ICT (Future-ICT 2019) in conjunction with the 4th International Symposium on Mobile Internet Security (MobiSec 2019) was held on 17–19 October 2019 in Taichung, Taiwan. The symposium provided academic and industry professionals an opportunity to discuss the latest issues and progress in advancing smart applications based on future ICT and its relative security. The symposium aimed to publish high-quality papers strictly related to the various theories and practical applications concerning advanced smart applications, future ICT, and related communications and networks. It was expected that the symposium and its publications would be a trigger for further related research and technology improvements in this field

    SPATIAL TRANSFORMATION PATTERN DUE TO COMMERCIAL ACTIVITY IN KAMPONG HOUSE

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    ABSTRACT Kampung houses are houses in kampung area of the city. Kampung House oftenly transformed into others use as urban dynamics. One of the transfomation is related to the commercial activities addition by the house owner. It make house with full private space become into mixused house with more public spaces or completely changed into full public commercial building. This study investigate the spatial transformation pattern of the kampung houses due to their commercial activities addition. Site observations, interviews and questionnaires were performed to study the spatial transformation. This study found that in kampung houses, the spatial transformation pattern was depend on type of commercial activities and owner perceptions, and there are several steps of the spatial transformation related the commercial activity addition. Keywords: spatial transformation pattern; commercial activity; owner perception, kampung house; adaptabilit

    2018 FSDG Combined Abstracts

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    https://scholarworks.gvsu.edu/fsdg_abstracts/1000/thumbnail.jp

    Science at the environmental research station Schneefernerhaus / Zugspitze

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    Das Buch enthält 22 Aufsätze, in denen die in der Forschungsstation Schneefernerhaus / Zugspitze aktiven Forscherinnen und Forscher ihre Arbeitsgebiete und bisherige Ergebnisse vorstellen. Die Aufsätze sind dabei so konzipiert, dass das Buch auch für die universitäre Lehre eingesetzt werden kann
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