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Table 6 Computational complexity overheads of SVM prediction

From: CU splitting early termination based on weighted SVM

Sequence

QP

Encode time (s)

Depth 0 (s)

Depth 1 (s)

Depth 2 (s)

Total SVM (s)

Percentage (%)

Basketball drive

22

26623.89

55.13

299.35

603.01

957.50

3.60

27

17178.92

60.57

130.78

195.82

387.16

2.25

32

12863.57

53.95

91.44

75.88

221.27

1.72

37

10754.91

57.71

59.57

23.91

141.18

1.31

BQTerrace

22

38162.54

64.27

355.10

1260.28

1679.66

4.40

27

16533.07

70.44

172.71

182.48

425.63

2.57

32

10971.15

64.40

85.81

50.90

201.10

1.83

37

8600.12

69.38

35.46

12.28

117.13

1.36

Cactus

22

23983.84

53.70

294.53

681.30

1029.52

4.29

27

14079.50

59.71

123.27

163.39

346.38

2.46

32

10797.25

54.29

87.95

69.85

212.10

1.96

37

8967.79

58.32

55.40

20.64

134.36

1.50

Kimono

22

10746.46

26.03

141.21

284.47

451.71

4.20

27

6743.09

27.98

62.31

90.87

181.15

2.69

32

4778.21

25.67

43.66

13.07

82.40

1.72

37

4217.04

27.51

29.98

3.29

60.78

1.44

ParkScene

22

9920.39

24.85

138.25

232.19

395.30

3.98

27

6248.77

27.02

62.18

68.37

157.57

2.52

32

4695.61

25.44

39.24

25.83

90.52

1.93

 

37

3809.69

27.52

21.49

7.26

56.27

1.48