Path Relinking Particle Filter for Human Body Pose Estimation
نویسندگان
چکیده
This paper introduces the Path Relinking Particle Filter (PRPF) algorithm for improving estimation problems in human motion capture. PRPF hybridizes both Particle Filter and Path Relinking frameworks. The proposed algorithm increases the performance of general Particle Filter by improving the quality of the estimate, adapting computational load to problem constraints and reducing the number of required evaluations of the weighting function. We have applied the PRPF algorithm to 2D human pose estimation. Experimental results show that PRPF drastically reduces the MSE value to obtain the set of markers with respect to Condensation and Sampling Importance Resampling (SIR) algorithms.
منابع مشابه
Combining Particle filter and Population-Based Metaheuristics for Visual Articulated Motion Tracking
Visual tracking of articulated motion is a complex task with high computational costs. Because of the fact that articulated objects are usually represented as a set of linked limbs, tracking is performed with the support of a model. Model-based tracking allows determining object pose in an effortless way and handling occlusions. However, the use of articulated models generates a multidimensiona...
متن کامل2D Human Tracking by Efficient Model Fitting Using a Path Relinking Particle Filter
INTRODUCTION: Automatic visual analysis of human motion is an active research topic in Computer Vision and its interest has been growing in the last decade. Visual analysis of human movement is used in the fields of Medical, Occupational and Sports Biomechanics. The main purpose of this staudy is to present a 2D model-based Path Relinking Particle Filter (PRPF) algorithm for human motion tracki...
متن کاملAppearance-based Person Tracking and 3d Pose Estimation of Upper-body and Head
In the field of human-robot interaction (HRI), recognition of humans in a robot’s surroundings is a crucial task. Besides the localization, the estimation of a person’s 3D pose based on monocular camera images is a challenging problem on a mobile platform. For this purpose, an appearancebased approach, using a 3D model of the human upper body, has been developed end experimentally investigated....
متن کاملRao-Blackwellized Particle Filter for Human Appearance and Position Tracking
In human motion analysis, the joint estimation of appearance, body pose and location parameters is not always tractable due to its huge computational cost. In this paper, we propose a Rao-Blackwellized Particle Filter for addressing the problem of human pose estimation and tracking. The advantage of the proposed approach is that RaoBlackwellization allows the state variables to be splitted into...
متن کاملFeature-based Annealing Particle Filter for Robust Body Pose Estimation
This paper presents a new annealing method for particle filtering in the context of body pose estimation. The feature-based annealing is inferred from the weighting functions obtained with common image features used for the likelihood approximation. We introduce a complementary weighting function based on the foreground extraction and we balance the different measures through the annealing laye...
متن کامل