Home People Research Publications Demos
         
News Jobs Prospective
Students
About Internal

Discriminant Saliency Detection Examples for PASCAL 2006 Object Categories


This page presents examples of the use of DSD as a focus-of-attention mechanism. BU interest points, produced by standard computer vision operators, are pruned by the top-down discriminant saliency detector (DSD). The results are shown at 40% recall rate (see the main demo page for more details). The value of precision is also listed below each example. Each circle in the image represents the location and the size of a salient point. The white color indicates the points which fall inside the segmentation ground truth (the bounding box marked on the original image), while black indicates the opposite.


Person


1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

1.00

0.99

0.99

0.99

0.99

0.99

0.99

0.99

0.99

0.99

0.99

0.99

0.99

0.99

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.98

0.97

0.97

0.97

0.97

0.97

0.97

0.97

0.97

0.97

0.97

0.96

0.96

0.96

0.96

0.96

0.96

0.96

0.96

0.96

0.95

0.95

0.95

0.95

0.95

0.95

0.95

0.95

0.94

0.94

0.94

0.94

0.93

0.93

0.93

0.93

0.93

0.92

0.92

0.92

0.92

0.92

0.92

0.92

0.92

0.91

0.91

0.91

0.91

0.91

0.90

0.90

0.90

0.89

0.89

0.89

0.89

0.89

0.89

0.88

0.88

0.88

0.88

0.87

0.87

0.86

0.86

0.86

0.84

0.84

0.84

0.84

0.84

0.84

0.84

0.83

0.83

0.82

0.82

0.82

0.82

0.82

0.81

0.81

0.81

0.80

0.80

0.80

0.80

0.80

0.79

0.79

0.78

0.78

0.78

0.77

0.77

0.77

0.77

0.77

0.77

0.77

0.76

0.76

0.75

0.75

0.75

0.75

0.75

0.74

0.74

0.74

0.74

0.74

0.74

0.74

0.73

0.73

0.73

0.73

0.73

0.73

0.72

0.72

0.72

0.72

0.72

0.72

0.71

0.71

0.71

0.71

0.71

0.70

0.70

0.70

0.70

0.69

0.69

0.69

0.69

0.69

0.69

0.69

0.69

0.69

0.69

0.68

0.68

0.68

0.68

0.68

0.68

0.68

0.68

0.68

0.67

0.67

0.67

0.67

0.66

0.66

0.66

0.65

0.65

0.65

0.65

0.65

0.65

0.65

0.64

0.64

0.63

0.63

0.63

0.62

0.61

0.61

0.61

0.61

0.61

0.61

0.61

0.61

0.61

0.61

0.61

0.60

0.60

0.60

0.60

0.59

0.59

0.58

0.58

0.58

0.58

0.57

0.57

0.57

0.57

0.57

0.56

0.56

0.55

0.55

0.54

0.54

0.53

0.53

0.53

0.53

0.53

0.52

0.52

0.52

0.52

0.52

0.52

0.52

0.52

0.52

0.52

0.51

0.51

0.51

0.51

0.51

0.51

0.51

0.50

0.50

0.50

0.50

0.50

0.50

0.50

0.49

0.49

0.49

0.49

0.49

0.48

0.48

0.47

0.47

0.47

0.47

0.47

0.47

0.46

0.46

0.46

0.46

0.45

0.45

0.45

0.45

0.44

0.44

0.44

0.43

0.43

0.43

0.43

0.43

0.42

0.41

0.40

0.40

0.40

0.40

0.40

0.39

0.39

0.39

0.39

0.38

0.38

0.38

0.38

0.38

0.38

0.37

0.37

0.37

0.37

0.37

0.37

0.37

0.36

0.35

0.35

0.35

0.35

0.35

0.34

0.34

0.34

0.34

0.33

0.33

0.33

0.33

0.31

0.31

0.31

0.31

0.31

0.31

0.30

0.30

0.29

0.29

0.29

0.28

0.28

0.28

0.27

0.27

0.27

0.27

0.26

0.26

0.26

0.25

0.25

0.25

0.25

0.24

0.24

0.24

0.24

0.24

0.24

0.23

0.23

0.23

0.23

0.22

0.22

0.22

0.22

0.22

0.21

0.21

0.20

0.20

0.20

0.19

0.19

0.18

0.18

0.18

0.18

0.17

0.17

0.17

0.17

0.17

0.17

0.17

0.16

0.16

0.16

0.16

0.15

0.15

0.15

0.15

0.14

0.14

0.13

0.13

0.12

0.11

0.11

0.11

0.10

0.10

0.10

0.10

0.10

0.10

0.10

0.10

0.09

0.09

0.08

0.08

0.08

0.08

0.08

0.07

0.07

0.07

0.07

0.07

0.07

0.07

0.06

0.06

0.06

0.05

0.05

0.05

0.05

0.05

0.05

0.04

0.04

0.04

0.04

0.03

0.03

0.03

0.03

0.03

0.03

0.02

0.02

0.02

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.00





© SVCL