A COMPARISON AND EVALUATION OF MOTION INDEXING ...

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oundary when a valley in H is followed by a peak. We also take into account the difference between the valley and the peak to avoid false segments. This difference should be greater than some threshold R. The value of the threshold is chosen by the following equation (2.9): 24 R = Hmax − Hmin , (2.9) 10 where Hmax and Hmin are the maximum and minimum possible values of H. If the value of R is increased, it results in fewer segments that correspond to more distinct behaviors. Whereas if R is decreased, finer segmentation happens. To find the next boundary, the whole algorithm is restarted on the rest of the motion. The output of this technique is the same as the first one: The segment boundaries in terms of their frame numbers. 2.1.5 Indexing of Segments Segments are obtained as a result of the above segmentation techniques for a motion sequence. The indexing of two motion sequences involves the indexing of their respective segments. Therefore, indexing uses the information retrieved during the PCA analysis step of segmentation. When all segments are derived, we store the dimension r, the start frame, and the end frame for each segment. Our algorithm for indexing can be described as: 1. Combine two segments from different motions by concatenating the second segment to the first segment. Suppose the first segment is a m × D matrix and the second segment is a n×D matrix, the combined segment becomes a (m+n)×D matrix. Then use the r1 from the first segment to calculate the preserved information , Er1, for the combined segment.
2. Similarly combine the two segments by concatenating the first segment to the end of second segment. Then use the r2 from second segment to calculate the preserved information, Er2, for the combined segment. 3. If Er1 is equal to Er2 and both Er1 and Er2 are greater than the threshold τ, then it is a match, otherwise, it is not a match. 25
Page 1 and 2: A COMPARISON AND EVALUATION OF MOTI
Page 3 and 4: To my mom, dad, brother, friends an
Page 5 and 6: ABSTRACT A COMPARISON AND EVALUATIO
Page 7 and 8: TABLE OF CONTENTS ACKNOWLEDGEMENTS
Page 9 and 10: LIST OF FIGURES Figure Page 1.1 Ske
Page 11 and 12: CHAPTER 1 INTRODUCTION Animation is
Page 13 and 14: • Segmentation: The motion captur
Page 15 and 16: In several applications, like a mod
Page 17 and 18: provide fast interpolation but do n
Page 19 and 20: • Frame: Each slice of time of a
Page 21 and 22: Figure 1.1: Skeleton with bone name
Page 23 and 24: Figure 1.4: Snapshot of a sample AM
Page 25 and 26: CHAPTER 2 PCA-BASED TECHNIQUES In t
Page 27 and 28: The first step in a PCA analysis is
Page 29 and 30: of dimensions needed to represent t
Page 31 and 32: The PCA-SVD algorithm finds the val
Page 33: where Vr is a matrix with the first
Page 37 and 38: joints are known for every pose. He
Page 39 and 40: motion. Figure 3.1: Result of boole
Page 41 and 42: 2. Feature functions describing an
Page 43 and 44: F -equivalent if the corresponding
Page 45 and 46: 3.1.6.1 Inverted File Index Inverte
Page 47 and 48: the same set of exact hits. Figure
Page 49 and 50: CHAPTER 4 DYNAMIC TIME WARPING TECH
Page 51 and 52: Figure 4.1: Result of DTW technique
Page 53 and 54: operator \ to determine the relatio
Page 55 and 56: zmin = ¯z + ¯x ′ · sin(θmin)
Page 57 and 58: CHAPTER 5 EXPERIMENTS AND RESULTS W
Page 59 and 60: 5.2 Indexing Accuracy Testing To ev
Page 61 and 62: Figure 5.3: False positives for PCA
Page 63 and 64: Figure 5.5: False positives for PPC
Page 65 and 66: Figure 5.7: False positives for Fea
Page 67 and 68: Figure 5.9: False positives for DTW
Page 69 and 70: Figure 5.11: False positives for DT
Page 71 and 72: Figure 5.13: False Negatives detect
Page 73 and 74: DTW[18]. DTW matching can also be i
Page 75 and 76: Animation techniques can be broadly
Page 77 and 78: directly modified or manipulated by
Page 79 and 80: B.1 Breif History Human beings are
Page 81 and 82: B.2 Motion Capture Technologies 1.
Page 83 and 84: (b) Active markers: Markers have on
Page 85 and 86:
• Capture of movement: Subject we
Page 87 and 88:
animation abilities, it can be help
Page 89 and 90:
74 09 127 23 138 19 141 14 75 19 79
Page 91 and 92:
10 04 walk with hands moving more 0
Page 93 and 94:
118 05 jump 118 06 jump 118 07 jump
Page 95 and 96:
143 25 waiving 143 08 jumping twist
Page 97 and 98:
[9] A. J. Hanson, “Visualizing qu
Page 99:
BIOGRAPHICAL STATEMENT Harnish Bhat
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