Английская грамматика
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Grouplet: A Structured Image Representation for Recognizing Human and
Grouplet: A Structured Image Representation for Recognizing Human and
Grouplet: A Structured Image Representation for Recognizing Human and
Grouplet: A Structured Image Representation for Recognizing Human and
Grouplet: A Structured Image Representation for Recognizing Human and
Grouplet: A Structured Image Representation for Recognizing Human and
Grouplet: A Structured Image Representation for Recognizing Human and
Grouplet: A Structured Image Representation for Recognizing Human and
Human-Object Interaction
Human-Object Interaction
Human-Object Interaction
Human-Object Interaction
Human-Object Interaction
Human-Object Interaction
Human-Object Interaction
Human-Object Interaction
Human-Object Interaction
Human-Object Interaction
Human-Object Interaction
Human-Object Interaction
Background: Human-Object Interaction
Background: Human-Object Interaction
Background: Human-Object Interaction
Background: Human-Object Interaction
Background: Human-Object Interaction
Background: Human-Object Interaction
Background: Human-Object Interaction
Background: Human-Object Interaction
Background: Human-Object Interaction
Background: Human-Object Interaction
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Recognizing Human-Object Interaction is Challenging
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet: our intuition
Grouplet representation (e
Grouplet representation (e
Grouplet representation (e
Grouplet representation (e
Grouplet representation (e
Grouplet representation (e
Grouplet representation (e
Grouplet representation (e
Grouplet representation (e
Grouplet representation (e
Grouplet representation
Grouplet representation
Grouplet representation
Grouplet representation
Grouplet representation
Grouplet representation
Grouplet representation
Grouplet representation
Grouplet representation
Grouplet representation
A “Space” of Grouplets
A “Space” of Grouplets
A “Space” of Grouplets
A “Space” of Grouplets
A “Space” of Grouplets
A “Space” of Grouplets
A “Space” of Grouplets
A “Space” of Grouplets
A “Space” of Grouplets
A “Space” of Grouplets
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
People-Playing-Musical-Instruments (PPMI) Dataset
Recognition Tasks on People-Playing-Musical-Instruments (PPMI) Dataset
Recognition Tasks on People-Playing-Musical-Instruments (PPMI) Dataset
Recognition Tasks on People-Playing-Musical-Instruments (PPMI) Dataset
Recognition Tasks on People-Playing-Musical-Instruments (PPMI) Dataset
Recognition Tasks on People-Playing-Musical-Instruments (PPMI) Dataset
Recognition Tasks on People-Playing-Musical-Instruments (PPMI) Dataset
Recognition Tasks on People-Playing-Musical-Instruments (PPMI) Dataset
Recognition Tasks on People-Playing-Musical-Instruments (PPMI) Dataset
Recognition Tasks on People-Playing-Musical-Instruments (PPMI) Dataset
Recognition Tasks on People-Playing-Musical-Instruments (PPMI) Dataset
Classification: Playing Different Instruments
Classification: Playing Different Instruments
Classification: Playing Different Instruments
Classification: Playing Different Instruments
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Classifying Playing vs
Detecting people playing musical instruments
Detecting people playing musical instruments
Detecting people playing musical instruments
Detecting people playing musical instruments
Detecting people playing musical instruments
Detecting people playing musical instruments
Detecting people playing musical instruments
Detecting people playing musical instruments
Detecting people playing musical instruments
Detecting people playing musical instruments
Detecting people playing musical instruments
Detecting people playing musical instruments
Examples of Mined Grouplets
Examples of Mined Grouplets
Examples of Mined Grouplets
Examples of Mined Grouplets
Examples of Mined Grouplets
Examples of Mined Grouplets
Examples of Mined Grouplets
Examples of Mined Grouplets
Conclusion
Conclusion
Thanks to
Thanks to
Thanks to
Thanks to
Thanks to
Thanks to
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1Grouplet: A Structured Image 152-Grouplet). Gaussian distribution. Visual
Representation for Recognizing Human and codewords. Notations. I: Image. P:
Object Interactions. Bangpeng Yao and Li Reference point in the image. ?: Grouplet.
Fei-Fei Computer Science Department, ?i: Feature unit. ?(?,I): Matching score
Stanford University. of ? and I. ?(?i,I): Matching score of ?i
{bangpeng,feifeili}@cs.stanford.edu. 1. and I. For an image patch: ?(x): Image
2Human-Object Interaction. Playing neighborhood of x. ?: A small shift of the
saxophone. Human. Not playing saxophone. location. Matching score between ? and I.
Saxophone. 2. Matching score between ?i and I. Codeword
3Human-Object Interaction. Robots assignment score. Gaussian density value.
interact with objects. Automatic sports Codeword assignment score. Gaussian
commentary. Medical care. “Kobe is dunking density value. Ai: Visual codeword; xi:
the ball.”. 3. Image location; ?i: Variance of spatial
4Background: Human-Object Interaction. distribution. a?: Its visual appearance;
To be done. context. Schneiderman & x?: Its image location. 15.
Kanade, 2000 Viola & Jones, 2001 Huang 16Grouplet representation. Playing
et al, 2007 Papageorgiou & Poggio, saxophone. Other interactions. Part-based
2000 Wu & Nevatia, 2005 Dalal & configuration Co-occurrence
Triggs, 2005 Mikolajczyk et al, 2005 Leibe Discriminative. matching score: 0.6.
et al, 2005 Bourdev & Malik, 2009 matching score: 0.4. matching score: 0.0.
Felzenszwalb & Huttenlocher, 2005 Ren matching score: 0.1. 16.
et al, 2005 Ramanan, 2006 Ferrari et al, 17Grouplet representation. Part-based
2008 Yang & Mori, 2008 Andriluka et configuration Co-occurrence Discriminative
al, 2009 Eichner & Ferrari, 2009. Dense. All possible combinations of
Lowe, 1999 Belongie et al, 2002 Fergus et feature units. Densely sample image
al, 2003 Fei-Fei et al, 2004 Berg & locations. Many possible spatial
Malik, 2005 Felzenszwalb et al, 2005 distributions. All possible Codewords.
Grauman & Darrell, 2005 Sivic et al, 1-grouplet. 2-grouplet. 3-grouplet. 17.
2005 Lazebnik et al, 2006 Zhang et al, 18Outline. Intuition of Grouplet
2006 Savarese et al, 2007 Lampert et al, Representation Grouplet Feature
2008 Desai et al, 2009 Gehler & Representation Using Grouplet for
Nowozin, 2009. Gupta et al, 2009. Yao Recognition Dataset & Experiments
& Fei-Fei, 2010a. Yao & Fei-Fei, Conclusion. 18.
2010b. Murphy et al, 2003 Hoiem et al, 19A “Space” of Grouplets. 19.
2006 Shotton et al, 2006. Rabinovich et 20A “Space” of Grouplets. 20.
al, 2007 Heitz & Koller, 2008 Divvala 21A “Space” of Grouplets. 21.
et al, 2009. vs. 4. 22A “Space” of Grouplets. On background.
5Background: Human-Object Interaction. Shared by different interactions. 22.
To be done. context. Schneiderman & 23We only need discriminative Grouplets.
Kanade, 2000 Viola & Jones, 2001 Huang Number of feature units: N. N is large
et al, 2007 Papageorgiou & Poggio, (192200). Number of Grouplets: 2N very
2000 Wu & Nevatia, 2005 Dalal & large space. On background. Shared by
Triggs, 2005 Mikolajczyk et al, 2005 Leibe different interactions. Large ?(?,I).
et al, 2005 Bourdev & Malik, 2009 Small ?(?,I). Large ?(?,I). Small ?(?,I).
Felzenszwalb & Huttenlocher, 2005 Ren 23. 23.
et al, 2005 Ramanan, 2006 Ferrari et al, 24Obtaining discriminative grouplets for
2008 Yang & Mori, 2008 Andriluka et a class. Apriori Mining. Mine 1000~2000
al, 2009 Eichner & Ferrari, 2009. grouplets, only need to evaluate (2~100)?N
Lowe, 1999 Belongie et al, 2002 Fergus et grouplets. Obtain grouplets with large
al, 2003 Fei-Fei et al, 2004 Berg & ?(?,I) on the class. Remove grouplets with
Malik, 2005 Felzenszwalb et al, 2005 large ?(?,I) from other classes. Number of
Grauman & Darrell, 2005 Sivic et al, feature units: N. N is large (192200).
2005 Lazebnik et al, 2006 Zhang et al, Number of Grouplets: 2N very large space.
2006 Savarese et al, 2007 Lampert et al, Selected 1-grouplets. Candidate
2008 Desai et al, 2009 Gehler & 2-grouplets. [Agrawal & Srikant,
Nowozin, 2009. Gupta et al, 2009. Yao 1994]. 24.
& Fei-Fei, 2010a. Yao & Fei-Fei, 25Using Grouplets for Classification.
2010b. Murphy et al, 2003 Hoiem et al, SVM. Discriminative grouplets. 25.
2006 Shotton et al, 2006. Rabinovich et 26Outline. Intuition of Grouplet
al, 2007 Heitz & Koller, 2008 Divvala Representation Grouplet Feature
et al, 2009. vs. 5. Representation Using Grouplet for
6Outline. Intuition of Grouplet Recognition Dataset & Experiments
Representation Grouplet Feature Conclusion. 26.
Representation Using Grouplet for 27People-Playing-Musical-Instruments
Recognition Dataset & Experiments (PPMI) Dataset.
Conclusion. 6. http://vision.stanford.edu/resources_links
7Outline. Intuition of Grouplet html. PPMI+. PPMI-. Normalized image (200
Representation Grouplet Feature images each interaction). Original image.
Representation Using Grouplet for # Image: # Image: (172). (191). (177).
Recognition Dataset & Experiments (179). (200). (198). (185). (133). (149).
Conclusion. 7. (188). (167). (148). (169). (164). 27.
8Recognizing Human-Object Interaction 28Recognition Tasks on
is Challenging. Reference image: playing People-Playing-Musical-Instruments (PPMI)
saxophone. Different pose (or viewpoint). Dataset. Classification. Detection.
Different lighting. Different background. Playing different instruments. Playing vs.
Different instrument, similar pose. Same Not playing. For each interaction, 100
object (saxophone), different training and 100 testing images. vs. vs.
interactions. 8. 28.
9Grouplet: our intuition. Bag-of-words. 29Classification: Playing Different
Spatial pyramid. Part-based. Grouplet Instruments. 7-class classification on
Representation: Thomas & Malik, 2001 PPMI+ images. SPM: [Lazebnik et al, 2006]
Csurka et al, 2004 Fei-Fei & Perona, DPM: [Felzenszwalb et al, 2008]
2005 Sivic et al, 2005. Grauman & Constellation: [Fergus et al, 2003]
Darrell, 2005 Lazebnik et al, 2006. Weber [Niebles & Fei-Fei, 2007]. 29.
et al, 2000 Fergus et al, 2003 Leibe et 30Classifying Playing vs. Not playing.
al, 2004 Felzenszwalb et al, 2005 Bourdev Seven 2-class classification problem;
& Malik, 2009. 9. PPMI+ vs. PPMI- for each instrument.
10Grouplet: our intuition. Capture the Bassoon. Erhu. Flute. French horn.
subtle difference in human-object Saxophone. Violin. Average PPMI+ images.
interactions. Part-based configuration Average PPMI- images. 30.
Co-occurrence Discriminative Dense. 31Classifying Playing vs. Not playing.
Grouplet Representation: 10. Seven 2-class classification problem;
11Outline. Intuition of Grouplet PPMI+ vs. PPMI- for each instrument.
Representation Grouplet Feature Guitar. Average PPMI+ images. Average
Representation Using Grouplet for PPMI- images. 31.
Recognition Dataset & Experiments 32Detecting people playing musical
Conclusion. 11. instruments. Procedure: Face detection
12Grouplet representation (e.g. with a low threshold; Crop and normalize
2-Grouplet). Gaussian distribution. Visual image regions; 8-class classification. 7
codewords. Notations. I: Image. P: classes of playing instruments; Another
Reference point in the image. ?: Grouplet. class of not playing any instrument.
?i: Feature unit. Ai: Visual codeword; xi: Playing saxophone. No playing. No playing.
Image location; ?i: Variance of spatial 32.
distribution. 12. 33Detecting people playing musical
13Grouplet representation (e.g. instruments. Area under the
2-Grouplet). Gaussian distribution. Visual precision-recall curve: Out method: 45.7%;
codewords. Notations. I: Image. P: Spatial pyramid: 37.3%. 33.
Reference point in the image. ?: Grouplet. 34Detecting people playing musical
?i: Feature unit. ?(?,I): Matching score instruments. Area under the
of ? and I. ?(?i,I): Matching score of ?i precision-recall curve: Out method: 45.7%;
and I. Matching score between ? and I. Spatial pyramid: 37.3%. False detection.
Matching score between ?i and I. Ai: Missed detection. 34. Playing French horn.
Visual codeword; xi: Image location; ?i: 35Examples of Mined Grouplets. Playing
Variance of spatial distribution. 13. bassoon: Playing saxophone: Playing
14Grouplet representation (e.g. violin: Playing guitar: 35.
2-Grouplet). Gaussian distribution. Visual 36Conclusion. The Next Talk. Holistic
codewords. Notations. I: Image. P: image-based classification. Detailed
Reference point in the image. ?: Grouplet. understanding and reasoning. Vs. Pose
?i: Feature unit. ?(?,I): Matching score estimation & object detection. [B. Yao
of ? and I. ?(?i,I): Matching score of ?i and L. Fei-Fei. “Grouplet: A structured
and I. For an image patch: ?(x): Image image representation for recognizing human
neighborhood of x. Matching score between and object interactions.” CVPR 2010.]. [B.
? and I. Matching score between ?i and I. Yao and L. Fei-Fei. “Modeling mutual
Codeword assignment score. Gaussian context of object and human pose in
density value. Ai: Visual codeword; xi: human-object interaction activities.” CVPR
Image location; ?i: Variance of spatial 2010.]. 36.
distribution. a?: Its visual appearance; 37Thanks to. Juan Carlos Niebles, Jia
x?: Its image location. 14. Deng, Jia Li, Hao Su, Silvio Savarese, and
15Grouplet representation (e.g. anonymous reviewers. And You. 37.
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Английская грамматика

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