Titlebook: Articulated Motion and Deformable Objects; First International Hans-Hellmut Nagel,Francisco J. Perales López Conference proceedings 2000 S

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Recognition of Articulated Objects in SAR Imagesects. Using SAR scattering center locations and magnitudes as features, the invariance of these features with articulation (e.g. turret rotation of a tank) is shown for SAR signatures of actual vehicles from the MSTAR (Public) data. Although related to geometric hashing, our recognition approach is

幻想

A Robust Method for Motion Estimation in Image Sequencessurements by a neural recognition system, gross errors in the motion trajectories are avoided. Assuming correspondences between regions in successive images, a model based recursive estimation technique is applied to estimate the motion of the observed image region. For this purpose a Kalman filter

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Concerto

Visualization of Local Movements for Optimal Marker Positioningh cases, a skeleton model has to be identified to derive the joint motion. The optical technology has gained a large popularity due to the high precision of its marker position measurements. However, when it comes to building the skeleton frames out of the 3D marker positions, significant local skin

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Matching a Human Walking Sequence with a VRML Synthetic Modela VRML synthetic human model. The criteria used are part of a generic system for the analysis and synthesis of human motion. The system has two phases: an automatic or interactively supervised analysis phase where the motion is interpreted and a synthesis phase where the original motion is applied t

外貌

Model Adaptation and Posture Estimation of Moving Articulated Object Using Monocular Camera direct depth data, prior loose knowledge about the object, such as possible ranges of joint angles, lengths or widths of parts, and some relationships between them, are referred as system constraints. This paper first points out that the estimate by Kalman filter essentially converge to a wrong sta

BALK

Automatic Selection of , for Activity Recognitionmes from an activity sequence. We name these frames as the .. Moreover, we describe a pre-processing stage in order to build a robust representation for different human movements. Using this representation, we build an activity eigenspace that is used to obtain a probability measure. We use this mea

啜泣

Hans-Hellmut Nagel,Francisco J. Perales LópezIncludes supplementary material:

crumble

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/161987.jpg

Antarctic

https://doi.org/10.1007/107226043D; Computer vision; animation; deformable object; elastic deformations; image sequences; motion analysis;