Detecting orientation of digital images using face detection information
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
G06K-009/32
G06K-009/36
G06K-009/00
출원번호
UP-0482305
(2009-06-10)
등록번호
US-7844135
(2011-01-31)
발명자
/ 주소
Steinberg, Eran
Prilutsky, Yury
Corcoran, Peter
Bigioi, Petronel
Blonk, Leo
Gangea, Mihnea
Vertan, Constantin
출원인 / 주소
Tessera Technologies Ireland Limited
대리인 / 주소
Smith, Andrew V.
인용정보
피인용 횟수 :
14인용 특허 :
263
초록▼
A method of automatically establishing the correct orientation of an image using facial information. This method is based on the exploitation of the inherent property of image recognition algorithms in general and face detection in particular, where the recognition is based on criteria that is highl
A method of automatically establishing the correct orientation of an image using facial information. This method is based on the exploitation of the inherent property of image recognition algorithms in general and face detection in particular, where the recognition is based on criteria that is highly orientation sensitive. By applying a detection algorithm to images in various orientations, or alternatively by rotating the classifiers, and comparing the number of successful faces that are detected in each orientation, one may conclude as to the most likely correct orientation. Such method can be implemented as an automated method or a semi automatic method to guide users in viewing, capturing or printing of images.
대표청구항▼
What is claimed is: 1. A method of detecting an orientation of a digital image using statistical classifier techniques, comprising: using a processor; acquiring a digital image; cropping the digital image including selecting a facial region within the digital image excluding one or more regions of
What is claimed is: 1. A method of detecting an orientation of a digital image using statistical classifier techniques, comprising: using a processor; acquiring a digital image; cropping the digital image including selecting a facial region within the digital image excluding one or more regions of the digital image outside of said facial region to obtain a cropped image including said facial region; applying a set of face detection classifiers to the cropped image in a first orientation and determining a first level of match between said cropped image at said first orientation and said classifiers; rotating said cropped image to a second orientation to obtain a rotated image, applying the classifiers to said rotated image at said second orientation, and determining a second level of match between said rotated image at said second orientation and said classifiers; comparing said first and second levels of match between said classifiers and said cropped image and between said classifiers and said rotated image, respectively; and determining which of the first orientation and the second orientations has a greater probability of being a correct orientation based on which of the first and second levels of match, respectively, comprises a higher level of match. 2. The method of claim 1, further comprising, prior to applying said classifiers to said cropped image, color conversion, edge enhancement, blurring, sharpening, tone reproduction correction, exposure correction, gray scale transformation, region segmentation, further cropping, or combinations thereof. 3. The method of claim 1, wherein said classifiers comprise elliptical classifiers. 4. The method of claim 3, wherein said elliptical classifiers are oriented at known orientations. 5. The method of claim 1, wherein said classifiers correspond to regions of a detected face. 6. The method of claim 5, wherein said regions include an eye, two eyes, a nose, a mouth, or an entire face, or combinations thereof. 7. A method of detecting an orientation of a digital image using statistical classifier techniques comprising: using a processor; acquiring a digital image; cropping the digital image including selecting a facial region within the digital region excluding one or more regions of the digital image outside of said facial region to obtain a cropped image including said facial region; applying a set of face detection classifiers to the cropped image in a first orientation and determining a first level of match between said cropped image at said first orientation and said classifiers; rotating said set of classifiers a first predetermined amount, applying the classifiers rotated said first amount to said cropped image at said first orientation, and determining a second level of match between said cropped image at said first orientation and said classifiers rotated said first amount; comparing said first and second levels of match between said classifiers and said digital image and between said rotated classifiers and said cropped image, respectively; and determining which of the first and second levels of match, respectively, comprises a higher level of match in order to determine whether said first orientation is a correct orientation of said digital image. 8. The method of claim 7, further comprising, prior to applying said classifiers to said cropped image, color conversion, edge enhancement, blurring, sharpening, tone reproduction correction, exposure correction, gray scale transformation, region segmentation, further cropping, or combinations thereof. 9. The method of claim 7, wherein said classifiers comprise elliptical classifiers. 10. The method of claim 9, wherein said elliptical classifiers are initially oriented at known orientations and, when rotated by said first and second amounts, are rotated to different known orientations. 11. The method of claim 7, wherein said classifiers correspond to regions of a detected face. 12. The method of claim 11, wherein said regions include an eye, two eyes, a nose, a mouth, or an entire face, or combinations thereof. 13. One or more non-transitory computer readable storage devices having processor readable code embodied thereon, said processor readable code for programming one or more processors to perform a method of detecting an orientation of a digital image using statistical classifier techniques, the method comprising: applying a set of face detection classifiers to a digital image in a first orientation and determining a first level of match between said digital image at said first orientation and said classifiers; cropping the digital image including selecting a facial region within the digital image excluding one or more regions of the digital image outside of said facial region to obtain a cropped image including said facial region; applying said classifiers to said cropped image and determining said first level of match between said cropped image and said classifiers; rotating said cropped image to a second orientation, applying the classifiers to the rotated image at said second orientation, and determining a second level of match between the rotated image at said second orientation and said classifiers; comparing said first and second levels of match between said classifiers and said cropped image and between said classifiers and said rotated image, respectively; and determining which of the first orientation and the second orientations has a greater probability of being a correct orientation based on which of the first and second levels of match, respectively, comprises a higher level of match. 14. The one or more storage devices of claim 13, wherein the method further comprises, prior to applying said classifiers to said cropped image, color conversion, edge enhancement, blurring, sharpening, tone reproduction correction, exposure correction, gray scale transformation, region segmentation, further cropping, or combinations thereof. 15. The one or more storage devices of claim 13, wherein said classifiers comprise elliptical classifiers. 16. The one or more storage devices of claim 15, wherein said elliptical classifiers are oriented at known orientations. 17. The one or more storage devices of claim 13, wherein said classifiers correspond to regions of a detected face. 18. The one or more storage devices of claim 17, wherein said regions include an eye, two eyes, a nose, a mouth, or an entire face, or combinations thereof. 19. One or more non-transitory computer readable storage devices having processor readable code embodied thereon, said processor readable code for programming one or more processors to perform a method of detecting an orientation of a digital image using statistical classifier techniques, the method comprising: applying a set of face detection classifiers to a digital image in a first orientation and determining a first level of match between said digital image at said first orientation and said classifiers; cropping the digital image including selecting a facial region within the digital image excluding one or more regions of the digital image outside of said facial region to obtain a cropped image including said facial region; applying said classifiers to said cropped image and determining said first level of match between said cropped image and said classifiers; rotating said set of classifiers a first predetermined amount, applying the classifiers rotated said first amount to said cropped image at said first orientation, and determining a second level of match between said cropped image at said first orientation and said classifiers rotated said first amount; comparing said first and second levels of match between said classifiers and said cropped image and between said rotated classifiers and said cropped image, respectively; and determining which of the first and second levels of match, respectively, comprises a higher level of match in order to determine whether said first orientation is a correct orientation of said digital image. 20. The one or more storage devices of claim 19, wherein the method further comprises, prior to applying said classifiers to said cropped image, color conversion, edge enhancement, blurring, sharpening, tone reproduction correction, exposure correction, gray scale transformation, region segmentation, further cropping, or combinations thereof. 21. The one or more storage devices of claim 19, wherein said classifiers comprise elliptical classifiers. 22. The one or more storage devices of claim 21, wherein said elliptical classifiers are initially oriented at known orientations and, when rotated by said first and second amounts, are rotated to different known orientations. 23. The one or more storage devices of claim 19, wherein said classifiers correspond to regions of a detected face. 24. The one or more storage devices of claim 23, wherein said regions include an eye, two eyes, a nose, a mouth, or an entire face, or combinations thereof. 25. A portable digital camera, comprising: one or more optics and a sensor for acquiring a digital image, a processor, and one or more processor readable storage devices having processor readable code embodied thereon for programming the processor to perform a method of detecting an orientation of a digital image using statistical classifier techniques, wherein the method comprises: applying a set of face detection classifiers to a digital image in a first orientation and determining a first level of match between said digital image at said first orientation and said classifiers; cropping the digital image including selecting a facial region within the digital image excluding one or more regions of the digital image outside of said facial region to obtain a cropped image including said facial region; applying said classifiers to said cropped image and determining said first level of match between said cropped image and said classifiers; rotating said cropped image to a second orientation, applying the classifiers to the rotated image at said second orientation, and determining a second level of match between the rotated image at said second orientation and said classifiers; comparing said first and second levels of match between said classifiers and said cropped image and between said classifiers and said rotated image, respectively; and determining which of the first orientation and the second orientations has a greater probability of being a correct orientation based on which of the first and second levels of match, respectively, comprises a higher level of match. 26. The camera of claim 25, wherein the method further comprises, prior to applying said classifiers to said cropped image, color conversion, edge enhancement, blurring, sharpening, tone reproduction correction, exposure correction, gray scale transformation, region segmentation, further cropping, or combinations thereof. 27. The camera of claim 25, wherein said classifiers comprise elliptical classifiers. 28. The camera of claim 27, wherein said elliptical classifiers are oriented at known orientations. 29. The camera of claim 25, wherein said classifiers correspond to regions of a detected face. 30. The camera of claim 29, wherein said regions include an eye, two eyes, a nose, a mouth, or an entire face, or combinations thereof. 31. A portable digital camera, comprising: one or more optics and a sensor for acquiring a digital image, a processor, and one or more processor readable storage devices having processor readable code embodied thereon for programming the processor to perform a method of detecting an orientation of a digital image using statistical classifier techniques, wherein the method comprises: applying a set of face detection classifiers to a digital image in a first orientation and determining a first level of match between said digital image at said first orientation and said classifiers; cropping the digital image including selecting a facial region within the digital image excluding one or more regions of the digital image outside of said facial region to obtain a cropped image including said facial region; applying said classifiers to said cropped image and determining said first level of match between said cropped image and said classifiers; rotating said set of classifiers a first predetermined amount, applying the classifiers rotated said first amount to said cropped image at said first orientation, and determining a second level of match between said cropped image at said first orientation and said classifiers rotated said first amount; comparing said first and second levels of match between said classifiers and said cropped image and between said rotated classifiers and said cropped image, respectively; and determining which of the first and second levels of match, respectively, comprises a higher level of match in order to determine whether said first orientation is a correct orientation of said digital image. 32. The camera of claim 31, wherein the method further comprises, prior to applying said classifiers to said cropped image, color conversion, edge enhancement, blurring, sharpening, tone reproduction correction, exposure correction, gray scale transformation, region segmentation, further cropping, or combinations thereof. 33. The camera of claim 31, wherein said classifiers comprise elliptical classifiers. 34. The camera of claim 33, wherein said elliptical classifiers are initially oriented at known orientations and, when rotated by said first and second amounts, are rotated to different known orientations. 35. The camera of claim 31, wherein said classifiers correspond to regions of a detected face. 36. The camera of claim 35, wherein said regions include an eye, two eyes, a nose, a mouth, or an entire face, or combinations thereof.
연구과제 타임라인
LOADING...
LOADING...
LOADING...
LOADING...
LOADING...
이 특허에 인용된 특허 (263)
Suzuki Shinichi (Tokyo JPX) Yasukawa Seiichi (Kawasaki JPX) Sato Toshihiro (Yokohama JPX) Narisawa Tsutomu (Saitama JPX), A photo taking apparatus capable of making a photograph with flash by a flash device.
Taguchi, Yasunori; Ouchi, Natsuko; Izuka, Kazuhiro; Yuki, Yoshinori; Kataoka, Yoshihiro; Ida, Takashi, Apparatus and method for processing a photographic image using a stencil.
White,Timothy J.; Blanco,Felix; Gerard,Michael J.; Leem,Yojin; Kurtenbach,Thomas J.; Christoffel,Douglas W.; Delong,Kevin R.; Smith,Craig M., Apparatus and method for processing digital images having eye color defects.
Hutcheson Timothy L. (Los Gatos CA) Or Wilson (Santa Clara CA) Narayanan Venkatesh (Fremont CA) Mohan Subramaniam (Sunnyvale CA) Wohlmut Peter G. (Saratoga CA) Srinivasan Ramanujam (Sunnyvale CA) Hun, Apparatus for generating a feature matrix based on normalized out-class and in-class variation matrices.
Benati Paul J. (Webster NY) Gray Robert T. (Rochester NY) Cosgrove Patrick A. (Honeoye Falls NY), Automated detection and correction of eye color defects due to flash illumination.
Eleftheriadis Alexandros ; Jacquin Arnaud Eric, Automatic face and facial feature location detection for low bit rate model-assisted H.261 compatible coding of video.
Takiguchi Hideo (Yokohama JPX), Color image processing apparatus for extracting image data having predetermined color information from among inputted im.
Harshaw Robert C. (Dallas TX) Burkey Ronald S. (Dallas TX) Doell James T. (Dallas TX) Keith Dennis G. (Dallas TX), Computerized checklist with predetermined sequences of sublists which automatically returns to skipped checklists.
Nesterov, Victor Anatol'evich; Khvatov, Vladimir Alezandrovich; Lalyko, Leonid Borisovich; Zaklika, Kryzstof Antoni, Correction of “red-eye” effects in images.
Matsuo, Hideaki; Imagawa, Kazuyuki; Takata, Yuji; Baba, Naruatsu; Ejima, Toshiaki, Device and method for face image extraction, and recording medium having recorded program for the method.
Buhr John D. ; Goodwin Robert M. ; Koeng Frederick R. ; Rivera Jose E., Digital photofinishing system including scene balance, contrast normalization, and image sharpening digital image processing.
Peter Fellegara ; Richard W. Lourette ; Michael E. Miller ; Linda M. Antos ; Robert H. Hibbard, Electronic camera with quick review of last captured image.
Parulski Kenneth A. (Rochester NY) Napoli Thomas A. (Rochester NY) Lewis David M. (Waterport NY), Electronic still camera for capturing and categorizing images.
Kuchta Daniel W. (Brockport NY) Sucy Peter J. (Hamlin NY), Electronic still camera providing multi-format storage of full and reduced resolution images.
Steffens Johannes Bernhard ; Elagin Egor Valerievich ; Nocera Luciano Pasquale Agostino ; Maurer Thomas ; Neven Hartmut, Face recognition from video images.
Prasad K. Venkatesh (Cupertino CA) Stork David G. (Stanford CA), Facial feature extraction method and apparatus for a neural network acoustic and visual speech recognition system.
Hanna, Keith James; Burt, Peter J.; Peleg, Shmuel; Dixon, Douglas F.; Mishra, Deepam; Wixson, Lambert E.; Mandlebaum, Robert; Coyle, Peter; Herman, Joshua R., Fully automated iris recognition system utilizing wide and narrow fields of view.
Hirosawa, Masashi, Image combination device, image combination method, image combination program, and recording medium for combining images having at least partially same background.
Poggio Tomaso ; Beymer David ; Jones Michael ; Vetter Thomas,DEX, Image compression by pointwise prototype correspondence using shape and texture information.
Lu Daozheng (Buffalo Grove IL) Kiewit David A. (Palm Harbor FL) Zhang Jia (Mundelein IL), Market research method and system for collecting retail store and shopper market research data.
Brogliatti, Barbara Spencer; Grakal, Christopher; Janney, Lisa A.; O'Neil, Marisa B.; Smith, Thomas G., Method and apparatus for archiving in and retrieving images from a digital image library.
Anderson, Eric C.; Bernstein, John D.; Pavely, John F.; Alsing, Carl J., Method and apparatus for defining a panning and zooming path across a still image during movie creation.
Gorday, Robert Mark; Gorday, Paul Edward; Eaton, Eric Thomas; Sibecas, Salvador, Method and apparatus for limiting storage or transmission of visual information.
Bedell Jeffrey L. (Arlington MA) Cockroft Gregory (Santa Clara CA) Peters Eric C. (Carlisle MA) Warner William J. (Weston MA), Method and apparatus for manipulating digital video data.
Fujio Noguchi ; Kazuhiko Akaike JP; Setsuko Watanabe Blaszkowski ; Noriko Kotabe GB; Takashi Otani JP; Tadashi Kajiwara, Method and apparatus for providing favorite station and programming information in a multiple station broadcast system.
Steinberg, Eran; Corcoran, Peter; Prilutsky, Yury; Biglol, Petronel; Nanu, Florin, Method and apparatus for red-eye detection in an acquired digital image.
Tal Peter (53 Driftwood Dr. Port Washington NY 11050), Method and apparatus for uniquely identifying individuals by particular physical characteristics and security system uti.
Tajima, Johji, Method and device of light source discrimination, skin color correction, and color image correction, and storage medium thereof capable of being read by computer.
Zanzucchi,Peter John; Moroney, III,Richard Morgan; Aceti,John Gregory; Pletcher,Timothy Allen; Burstyn,Herschel Clement, Method and imager for detecting the location of objects.
Eckes,Christian; Kefalea,Efthimia; Von Der Malsburg,Chrstoph; P철tzsch,Michael; Rinne,Michael; Triesch,Jochen; Vorbr체ggen,Jan C., Method for recognizing objects in digitized images.
Steinberg,Eran; Prilutsky,Yury; Corcoran,Peter; Bigioi,Petronel, Method of improving orientation and color balance of digital images using face detection information.
Brunelli Roberto,ITX ; Mich Ornella,ITX, Method of storing and retrieving images of people, for example, in photographic archives and for the construction of id.
Ogrinc Michael A. (San Francisco CA) Card Robert A. (Palo Alto CA) Burns Chris R. (Mountain View CA) Clarke Charles P. (Los Altos CA) Collier Ronda L. (Scotts Valley CA) Collins Kevin M. (San Mateo C, Real time video image processing system.
Corcoran,Peter; Steinberg,Eran; Petrescu,Stefan; Drimbarean,Alexandru; Nanu,Florin; Pososin,Alexei; Bigioi,Petronel, Real-time face tracking in a digital image acquisition device.
Corcoran,Peter; Steinberg,Eran; Petrescu,Stefan; Drimbarean,Alexandru; Nanu,Florin; Pososin,Alexei; Bigioi,Petronel, Real-time face tracking in a digital image acquisition device.
Corcoran,Peter; Steinberg,Eran; Petrescu,Stefan; Drimbarean,Alexandru; Nanu,Florin; Pososin,Alexei; Biglol,Petronel, Real-time face tracking in a digital image acquisition device.
Ianculescu,Mihai; Bigioi,Petronel; Gangea,Mihnea; Petrescu,Stefan; Corcoran,Peter; Steinberg,Eran, Real-time face tracking in a digital image acquisition device.
Steinberg,Eran; Corcoran,Peter; Bigioi,Petronel; Pososin,Alexei; Drimbarean,Alexandru; Nanu,Florin; Petrescu,Stefan, Real-time face tracking in a digital image acquisition device.
Bortolussi Jay F. ; Cusack ; Jr. Francis J. ; Ehn Dennis C. ; Kuzeja Thomas M. ; Saulnier Michael S., Real-time facial recognition and verification system.
Okubo,Atsushi; Sabe,Kohtaro; Kawamoto,Kenta; Fukuchi,Masaki, Robot device and face identifying method, and image identifying device and image identifying method.
Maeda Yutaka (Kanagawa JPX) Kyoden Yasuhiro (Sagamihara JPX) Naruto Hirokazu (Higashiosaka JPX) Tanaka Yoshito (Sakai JPX) Shintani Dai (Sakai JPX) Nanba Katsuyuki (Osakasayama JPX), Still video camera having a printer capable of printing a photographed image in a plurality of printing modes.
Mashimo Yukio (Tokyo JA) Sakurada Nobuaki (Kanagawa JA) Ito Tadashi (Kanagawa JA) Ito Fumio (Kanagawa JA) Shinoda Nobuhiko (Tokyo JA), System for exposure measurement and/or focus detection by means of image senser.
Mashimo Yukio (Tokyo JPX) Sakurada Nobuaki (Kanagawa JPX) Ito Tadashi (Kanagawa JPX) Ito Fumio (Kanagawa JPX) Shinoda Nobuhiko (Tokyo JPX), System for exposure measurement and/or focus detection by means of image sensor.
Freeman William T. ; Leventon Michael E., System for reconstructing the 3-dimensional motions of a human figure from a monocularly-viewed image sequence.
Kuperstein Michael ; Kottas James A., System, method and application for the recognition, verification and similarity ranking of facial or other object patterns.
Wheeler Richard B. (Webster NY), Technique suited for use in multi-zone autofocusing cameras for improving image quality for non-standard display sizes a.
Kojima Kazuaki (Nagaokakyo JPX) Kuno Tetsuya (Nagaokakyo JPX) Sugiura Hiroaki (Nagaokakyo JPX) Yamada Takeshi (Nagaokakyo JPX), Video signal processor for detecting flesh tones in am image.
Jain Ramesh ; Horowitz Bradley ; Fuller Charles E. ; Gupta Amarnath ; Bach Jeffrey R. ; Shu Chiao-fe, Visual image database search engine which allows for different schema.
Corcoran, Peter; Bigioi, Petronel; Stec, Piotr, Face and other object detection and tracking in off-center peripheral regions for nonlinear lens geometries.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.