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6,575
Articulated body motion capture by annealed particle filtering
- In IEEE Conf. on Computer Vision and Pattern Recognition
, 2000
"... The main challenge in articulated body motion tracking is the large number of degrees of freedom (around 30) to be recovered. Search algorithms, either deterministic or stochastic, that search such a space without constraint, fall foul of exponential computational complexity. One approach is to intr ..."
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Cited by 494 (4 self)
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special preparation of subjects or restrictive assumptions. The principal contribution of this paper is the development of a modified particle filter for search in high dimensional configuration spaces. It uses a continuation principle, based on annealing, to introduce the influence of narrow peaks
Using Gaussian Process Annealing Particle Filter for 3D Human Tracking
"... Abstract. We present an approach for human body parts tracking in 3D with prelearned motion models using multiple cameras. Gaussian Process Annealing Particle Filter is proposed for tracking in order to reduce the dimensionality of the problem and to increase the tracker’s stability and robustness. ..."
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Cited by 13 (0 self)
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Abstract. We present an approach for human body parts tracking in 3D with prelearned motion models using multiple cameras. Gaussian Process Annealing Particle Filter is proposed for tracking in order to reduce the dimensionality of the problem and to increase the tracker’s stability and robustness
Tracking a walking person using activity-guided annealed particle filtering
- In F&G
, 2008
"... Tracking human pose using observations from less than three cameras is a challenging task due to ambiguity in the available image evidence. This work presents a method for tracking using a pre-trained model of activity to guide sampling within an Annealed Particle Filtering framework. The approach i ..."
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Cited by 3 (3 self)
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Tracking human pose using observations from less than three cameras is a challenging task due to ambiguity in the available image evidence. This work presents a method for tracking using a pre-trained model of activity to guide sampling within an Annealed Particle Filtering framework. The approach
Interacting and annealing particle filters: Mathematics and a recipe for applications
- J. OF MATHEMATICAL IMAGING AND VISION
, 2007
"... Interacting and annealing are two powerful strategies that are applied in different areas of stochastic modelling and data analysis. Interacting particle systems approximate a distribution of interest by a finite number of particles where the particles interact between the time steps. In computer v ..."
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Cited by 23 (9 self)
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vision, they are commonly known as particle filters. Simulated annealing, on the other hand, is a global optimization method derived from statistical mechanics. A recent heuristic approach to fuse these two techniques for motion capturing has become known as annealed particle filter. In order to analyze
On the Behaviour of Body Tracking with the Annealed Particle Filter in Realistic Conditions
, 2006
"... Articulated full-body tracking of high-dimensional 3D human figures is currently an active area of research. However, the vast majority of work has focused on tracking a person in controlled environments similar to dedicated marker-based motion-capture facilities. This means that many real-world con ..."
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Cited by 3 (0 self)
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-body tracking provides, such as action recognition or multi-person tracking. Hence this paper evaluates the behaviour of the annealed particle filter (APF – a widely-cited body tracking algorithm) with the goal of identifying and resolving the cause of failures in tracking under realistic conditions. A loose
Combination of annealing particle filter and belief propagation for 3D upper body tracking
, 2012
"... Abstract. 3D upper body pose estimation is a topic greatly studied by the computer vision society because it is useful in a great number of applications, mainly for human robots interactions including communications with companion robots. However there is a challenging problem: the complexity of cl ..."
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of classical algorithms that increases exponentially with the dimension of the vectors' state becomes too difficult to handle. To tackle this problem, we propose a new approach that combines several annealing particle filters defined independently for each limb and belief propagation method to add
Voxel based annealed particle filtering for markerless 3D articulated motion capture
- in Proceedings of the 3rd IEEE Conference on 3DTV (3DTV-CON ’09
, 2009
"... This paper presents a view-independent approach to markerless hu-man motion capture in low resolution sequences from multiple cal-ibrated and synchronized cameras. Redundancy among cameras is exploited to generate a 3D voxelized representation of the scene and a human body model (HBM) is introduced ..."
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Cited by 2 (1 self)
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towards analyzing these data. An annealed particle filtering scheme where every particle encodes an instance of the pose of the HBM is employed. Likeli-hood between particles and input data is performed using occupancy and surface information and kinematic constrains are imposed in the propagation step
Y.: Parallelized annealed particle filter for realtime marker-less motion tracking via heterogeneous computing
- In: ICPR
, 2012
"... Abstract We propose a parallelized Annealed Particle Filter method via heterogeneous computing (P-APF), to implement real-time marker-less motion tracking based on OpenCL framework. The overall computing procedure in P-APF is decomposed into several computational tasks with corresponding granularit ..."
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Cited by 1 (1 self)
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Abstract We propose a parallelized Annealed Particle Filter method via heterogeneous computing (P-APF), to implement real-time marker-less motion tracking based on OpenCL framework. The overall computing procedure in P-APF is decomposed into several computational tasks with corresponding
Automated pose estimation in 3D point clouds applying annealing particle filters and inverse kinematics on a gpu
- In CVPR Workshop
, 2010
"... lehment, arsic, rigoll @ tum.de Current experiments with HCIs have shown a high demand for more natural interaction paradigms. Gestures are thereby considered the most important cue besides speech. In order to recognize gestures it is necessary to extract meaningful motion features from the body. Up ..."
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Cited by 4 (0 self)
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lehment, arsic, rigoll @ tum.de Current experiments with HCIs have shown a high demand for more natural interaction paradigms. Gestures are thereby considered the most important cue besides speech. In order to recognize gestures it is necessary to extract meaningful motion features from the body. Up to now mostly marker based tracking systems are used in virtual reality environments, since these were traditionally more reliable than purely image based detection methods. However, markers tend to be distracting and cumbersome. Following recent advances in processing power, it becomes possible to use a camera system in order to obtain a depth image of the test subject, match it to a pre-defined body model, and thus track the body parts over time. We will present a fullbody system based on APF which enables full body tracking utilizing point clouds recorded with a 3D sensor. Further refinement is provided by a specially adapted inverse kinematics system. A GPU based implementation speeds up processing significantly and allows near real time performance. 1.
A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
- IEEE TRANSACTIONS ON SIGNAL PROCESSING
, 2002
"... Increasingly, for many application areas, it is becoming important to include elements of nonlinearity and non-Gaussianity in order to model accurately the underlying dynamics of a physical system. Moreover, it is typically crucial to process data on-line as it arrives, both from the point of view o ..."
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Cited by 2006 (2 self)
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of storage costs as well as for rapid adaptation to changing signal characteristics. In this paper, we review both optimal and suboptimal Bayesian algorithms for nonlinear/non-Gaussian tracking problems, with a focus on particle filters. Particle filters are sequential Monte Carlo methods based on point mass
Results 1 - 10
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6,575