598 research outputs found
Activity-conditioned continuous human pose estimation for performance analysis of athletes using the example of swimming
In this paper we consider the problem of human pose estimation in real-world
videos of swimmers. Swimming channels allow filming swimmers simultaneously
above and below the water surface with a single stationary camera. These
recordings can be used to quantitatively assess the athletes' performance. The
quantitative evaluation, so far, requires manual annotations of body parts in
each video frame. We therefore apply the concept of CNNs in order to
automatically infer the required pose information. Starting with an
off-the-shelf architecture, we develop extensions to leverage activity
information - in our case the swimming style of an athlete - and the continuous
nature of the video recordings. Our main contributions are threefold: (a) We
apply and evaluate a fine-tuned Convolutional Pose Machine architecture as a
baseline in our very challenging aquatic environment and discuss its error
modes, (b) we propose an extension to input swimming style information into the
fully convolutional architecture and (c) modify the architecture for continuous
pose estimation in videos. With these additions we achieve reliable pose
estimates with up to +16% more correct body joint detections compared to the
baseline architecture.Comment: 10 pages, 9 figures, accepted at WACV 201
Advances in Monocular Exemplar-based Human Body Pose Analysis: Modeling, Detection and Tracking
Esta tesis contribuye en el análisis de la postura del cuerpo humano a partir de secuencias de imágenes adquiridas con una sola cámara. Esta temática presenta un amplio rango de potenciales aplicaciones en video-vigilancia, video-juegos o aplicaciones biomédicas. Las técnicas basadas en patrones han tenido éxito, sin embargo, su precisión depende de la similitud del punto de vista de la cámara y de las propiedades de la escena entre las imágenes de entrenamiento y las de prueba. Teniendo en cuenta un conjunto de datos de entrenamiento capturado mediante un número reducido de cámaras fijas, paralelas al suelo, se han identificado y analizado tres escenarios posibles con creciente nivel de dificultad: 1) una cámara estática paralela al suelo, 2) una cámara de vigilancia fija con un ángulo de visión considerablemente diferente, y 3) una secuencia de video capturada con una cámara en movimiento o simplemente una sola imagen estática
VNect: Real-time 3D Human Pose Estimation with a Single RGB Camera
We present the first real-time method to capture the full global 3D skeletal
pose of a human in a stable, temporally consistent manner using a single RGB
camera. Our method combines a new convolutional neural network (CNN) based pose
regressor with kinematic skeleton fitting. Our novel fully-convolutional pose
formulation regresses 2D and 3D joint positions jointly in real time and does
not require tightly cropped input frames. A real-time kinematic skeleton
fitting method uses the CNN output to yield temporally stable 3D global pose
reconstructions on the basis of a coherent kinematic skeleton. This makes our
approach the first monocular RGB method usable in real-time applications such
as 3D character control---thus far, the only monocular methods for such
applications employed specialized RGB-D cameras. Our method's accuracy is
quantitatively on par with the best offline 3D monocular RGB pose estimation
methods. Our results are qualitatively comparable to, and sometimes better
than, results from monocular RGB-D approaches, such as the Kinect. However, we
show that our approach is more broadly applicable than RGB-D solutions, i.e. it
works for outdoor scenes, community videos, and low quality commodity RGB
cameras.Comment: Accepted to SIGGRAPH 201
Human action recognition from RGB-D frames
Scopo di questo lavoro è la creazione di un sistema client-server facilmente fruibile per la videosorveglianza tramite la telecamera Omnidome®.
Vengono impiegate tecnologie AJAX, PHP, HTML e C++ per la realizzazione di una interfaccia di prenotazione e controllo il più semplice ed intuitiva possibile, con gestione automatizzata della coda di utentiopenEmbargo per motivi di segretezza e di proprietà dei risultati e informazioni sensibil
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