Articulated Object Registration Using Simulated Physical Force/Moment for 3D Human Motion Tracking
نویسندگان
چکیده
In this paper, we present a 3D registration algorithm based on simulated physical force/moment for articulated human motion tracking. Provided with sparsely reconstructed 3D human surface points from multiple synchronized cameras, the tracking problem is equivalent to fitting the 3D model to the scene points. The simulated physical force/ moment generated by the displacement between the model and the scene points is used to align the model with the scene points in an Iterative Closest Points (ICP) [1] approach. We further introduce a hierarchical scheme for model state updating, which automatically incorporates human kinematic constraints. Experimental results on both synthetic and real data from several unconstrained motion sequences demonstrate the efficiency and robustness of our proposed method.
منابع مشابه
An efficient stochastic framework for 3D human motion tracking
In this paper, we present a stochastic framework for articulated 3D human motion tracking. Tracking full body human motion is a challenging task, because the tracking performance normally suffers from several issues such as self-occlusion, foreground segmentation noise and high computational cost. In our work, we use explicit 3D reconstructions of the human body based on a visual hull algorithm...
متن کامل3D Arm Motion Tracking for Home-based Rehabilitation
This paper presents a real-time hybrid solution to articulated 3D arm motion tracking for home-based rehabilitation by combining visual and inertial sensors. The Extended Kalman Filter (EKF) is used to fuse the different data modalities from two sensors and exploit complementary sensor characteristics. Due to the non-linear property of the arm motion tracking, upper limb geometry information an...
متن کاملRASKIN, RUDZSKY, RIVLIN: BODY-PART TRACKING AND ACTION CLASSIFICATION 1 3D Human Body-Part Tracking and Action Classification Using a Hierarchical Body Model
This paper presents a framework for hierarchical 3D articulated human body-part tracking and action classification. We introduce a Hierarchical Annealing Particle Filter (H-APF) algorithm, which applies nonlinear dimensionality reduction of the high dimensional data space to the low dimensional latent spaces combined with the dynamic motion model and the Hierarchical Human Body Model. The impro...
متن کاملLearning Kinematic Descriptions using SPARE: Simulated and Physical ARticulated Extendable dataset
Next generation robots will need to understand intricate and articulated objects as they cooperate in human environments. To do so, these robots will need to move beyond their current abilities—working with relatively simple objects in a task-indifferent manner—toward more sophisticated abilities that dynamically estimate the properties of complex, articulated objects. To that end, we make two ...
متن کاملA Study on Human Gaze Detection Based on 3D Eye Model
Robust fake iris detection p. 10 A study on fast Iris restoration based on focus checking p. 19 A spatio-temporal metric for dynamic mesh comparison p. 29 Facetoface : an isometric model for facial animation p. 38 Matching two-dimensional articulated shapes using generalized multidimensional scaling p. 48 Further developments in geometrical algorithms for ear biometrics p. 58 Composition of com...
متن کامل