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Table 2. Module percentage breakdown of the single-threaded articulated body tracker

in COMPUTER VISION ON MULTI-CORE PROCESSORS: ARTICULATED BODY TRACKING
by Trista P. Chen, Dmitry Budnikov, Christopher J. Hughes, Yen-kuang Chen
"... In PAGE 3: ...54 (Table 1). Table2 shows that tracking with APF takes up over 91% of the execution time for a single threaded run. This stage scales extremely well: 7.... ..."

Table 4: A comparison of the error norm between individual tracking methods and articulated tracking via kinematic sets

in Kinematic sets for real-time robust articulated object tracking
by Andrew I. Comport, Éric Marchand, François Chaumette 2006
"... In PAGE 26: ...Table 4: A comparison of the error norm between individual tracking methods and articulated tracking via kinematic sets When referring to the table in Table4 , it can be mentioned that for the hinge, track- ing failure is more easily observed in the image as the tracking continues without fully breaking down in the plots. Even so, the plot of the velocities shows different values to that of the articulated case.... ..."
Cited by 1

Table 1: Results for the tracking of body parts.

in Gait Classification with HMMs for Trajectories of Body Parts Extracted by Mixture Densities
by Dorthe Meyer, Josef Pösl, Heinrich Niemann 1998
Cited by 18

Table 1: Comparison between the geometry for two views of 1 rigid body motion and that for n rigid body motions.

in Segmentation of Dynamic Scenes from the Multibody Fundamental Matrix
by Rene Vidal, Stefano Soatto, Yi Ma, Shankar Sastry
"... In PAGE 4: ... 5.5 Summary of multibody geometry Table1 summarizes our theoretical development with a comparison of the geometric entities associated with two views of 1 rigid body motion and two views of n rigid body motions. Polynomial factorization Segmentation Epipolar transfer Veronese map PSfrag replacements x1 2 R3 x2 2 R3 n(x1) 2 RMn [x;y;z]T 7! [:::;xn1yn2zn3;:::]T F n(x1) 2 RMn xT 2 lk = 0 (x1;x2) 2 ith motion eT i lk = 0; or xT 2 Fix1 = 0 n(x)TF n(x1) = (xTl1) (xTln) (eT 1 l) (eT nl) = 0 lk 2 R3 fe1;:::;en 2 R3g fl1;:::;ln 2 R3g Figure 1: Transformation diagram associated with the segmentation of an image pair (x1;x2) in the presence of n motions.... ..."

Table 1: Results for the tracking of body parts.

in Gait Classification with HMMs for Trajectories of Body Parts Extracted by Mixture Densities
by Dorthe Meyer, Josef Pösl, Heinrich Niemann

Table I. Comparison between the geometry for two views of 1 rigid body motion and that for n rigid body motions.

in Two-View Multibody Structure from Motion
by Rene Vidal, Yi Ma, Stefano Soatto, Shankar Sastry 2004
Cited by 25

Table 5: Tableau for simulated motion tracking

in Experiments with Genetic Programming for Active Vision Tasks
by Jay Winkeler, B. S. Manjunath 1997
"... In PAGE 12: ...6. Table5 shows the complete list of parameters for these experiments. 7.... ..."
Cited by 1

Table 1. Comparison between the geometry for two views of 1 rigid-body motion and the geometry of n rigid-body motions.

in Two-view multibody structure from motion
by René Vidal, Yi Ma, Stefano Soatto 2004
Cited by 25

Table 1. Comparison between the geometry for two views of 1 rigid-body motion and the geometry of n rigid-body motions.

in Two-view multibody structure from motion
by René Vidal, Yi Ma, Stefano Soatto 2004
Cited by 25

Table I. Comparison between the geometry for two views of 1 rigid-body motion and the geometry of n rigid-body motions.

in Two-view multibody structure from motion
by René Vidal, Yi Ma, Stefano Soatto, Shankar Sastry 2004
Cited by 25
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