### Table 1: Motion models

"... In PAGE 5: ... Clearly, a 2-D motion model does not uniquely correspond to one 3-D model; identical 2-D motion models may result from di erent assumptions about 3-D motion, surface and camera projection models. Table1 summarizes some parametric models for 2-D motion and provides possible underlying assumptions. The rst four models are illustrated in Fig.... In PAGE 6: ...5 (a) (b) (c) (d) Figure 2: Examples of parametric motion vector elds (sampled) and corresponding motion-compensated predictions of a centered square: (a) translation; (b) a ne; (c) projective linear; and (d) quadratic. See Table1 for model descriptions. pable of describing arbitrary 2-D motion elds.... In PAGE 6: ... O -lattice vectors of the motion eld can be approximated by suitable interpolation of the sampled eld [65]. In general, the interpolation kernel H ( Table1 ) has a small support, such that a motion vector is usually interpolated from at most four samples. The frequently used bilinear inter- polation kernel is a tensor product of horizontal and vertical 1-D triangular kernels.... In PAGE 6: ... Therefore, it can be expected that such elds can be e ciently represented using linear transforms followed by zeroing of high frequency components. For example, the polynomial transform given in the last row of Table1... In PAGE 7: ... To capture these second-order e ects, each motion trajectory must be modeled explicitly. For example, it may be represented by two vectors: instantaneous velocity _ x and acceleration x [13]: x( ) x(t) + _ x(t)( ? t) + x(t) 2 ( ? t)2: (5) Such a temporal modeling can be applied in addition to the spatial modeling described thus far in Table1 . Although representation of motion trajectory elds rather than displacement elds is advantageous in certain applications, larger amounts of motion information must be processed and/or transmitted [13].... In PAGE 8: ...g., a ne; Table1... In PAGE 9: ...2.3 Motion of regions Between the two extremes above, one can nd methods that apply motion models from Table1 to image regions. The motivation is to insure a more accurate modeling (smaller approximation error (6)) of motion elds than in the global motion case and a reduced number of parameters in comparison with the dense motion.... In PAGE 10: ... Thus, a more general image partitioning is neces- sary. The reasoning is that for objects with su ciently smooth 3-D surface and 3-D motion, the induced 2-D motion elds in the image plane can be suitably described by models from Table1 if applied to the area of object projection. A natural image partitioning can be provided by the image acquisition process itself.... In PAGE 12: ... 4.a) for di erent regions of support: (a) block-based (16 16 blocks); (b) pixel-based (globally- smooth as in (17)); and (c,d) region-based with a ne motion model ( Table1 ). For details of the region-based algorithm, see [20].... ..."

### Table 2. Comparison of different methods to detect and track storm cells.

"... In PAGE 7: ... Furthermore, all storm related data is fully accessible in its archived form, without the need for restoration. Table2 summarizes some advantages and disadvantages of the different approaches. 4 Object detection and motion registration Now that radar images are stored in a gridfile, fast direct access to parts of a discrete object of interest (a single pixel of a storm cell) is possible.... ..."

### Table 1: Motion estimation results.

"... In PAGE 6: ... Again, the dashed line corresponds to the expected performance of the algorithm established using Monte Carlo simulation. Table1 summarizes the additional motion estimation results obtained from processing the approach and descent sequences obtained using 50 or 500 features and linear or linear+nonlinear motion estimation For the 50 feature descent sequence and the linear motion estimation algorithm, the average translation error is 0.... In PAGE 6: ... The approach sequence takes slightly longer to process because the larger image requires more time to detect features. The results in Table1 , show that in general the addition of the nonlinear motion estimation algorithm does not improve the results of motion estimation all that much. This is because for vertical descent, the motion computed using the linear algorithm is very constrained, so the results are very close to those obtained using the nonlinear algorithm.... In PAGE 7: ...otions (e.g., orbital motion) the nonlinear algorithm will result in improved motion estimation and should be used. Table1 also shows that adding features (50 vs. 500) does not improve motion estimation all that much.... ..."

### Table 6. Complexity of some Hough algorithms to detect ellipses

1997

Cited by 10

### Table 1: Experimental results for synthetic images Primitive Motion Detection

### Table 1: Results of the tracking: experiment, the number of switches between motion tracking (MT) module and motion detection (MD) module, the number of images tracked, and the amount of images in percent in which the distance of the center of gravity from the middle of the image is less than 5, 10, 20 pixels

1995

"... In PAGE 17: ....e. all possible changes of the contour of the train { based on the di erent viewing angles { and directions of motion could be recorded. In Table1 the results of the experiments are shown.In experiment 9 at the beginning of the experiment the moving object is not in the eld of view of the camera.... In PAGE 18: ... In all of the images the moving train is kept in the middle of the image. In column 2 of Table1 the stability of the automatic initialization and tracking with the active contour can be seen. A switch to the motion detection module will be done in the case of an error in the tracking module or after the automatic initialization.... ..."

Cited by 8

### Table 3.1 lists the nal motion parameters of the synthetic Blood Cells Sequence, which were obtained after one iteration step. The existing two motions are correctly recovered. The matrix parameters 1. 2, 3 and 4 are all zero indicating that the motions present are only translational. The primary motion and secondary motion2 are described as a translation of (5; ?3)T and (5; 0)T in the image plane, which are the exact parameters used to generate the sequence.

### Table 2 Detection performance of the algorithm based on the DWT.

"... In PAGE 3: ... This is because the size of an embolus, which validates the assumption of an embolus as a single scatterer, is much bigger than that of red blood cells. When the parameters defined above used to classify embolic signals, sensitivity and specificity achieved are give in Table2 . These results are as good or better than the other methods reported in [7].... ..."

### Table 2 Motion results for real images

"... In PAGE 2: ... After the final estimation, the location of 576 points are recovered with respect to frame 17. The recovered mo- tion parameters are listed in Table2 . While we do not have the complete set of ground truth, the exact values of angle of rotation and distance of translation are known.... ..."

### Table 1: Geometric Attack and Image Processing Distortion Types Parameters

"... In PAGE 4: ... 6.2 Robustness Testing In the robustness testing, we choose a set of geomet- ric transforms and common image processing operations as listed in Table1 to examine the robustness of the hash 3There are also other similar strategies to generate histogram-based hash, such as by computing the relative... In PAGE 6: ... Overall, the hash extraction method proposed in this pa- per can achieve a satisfactory performance for geometric at- tacks (due to the use of the histogram shape invariance) and noise-like image processing operations (due to the use of Gaussian low-pass fllter). For a set of manipulations listed in Table1 , the Hamming distance is less than 0.15.... ..."