Patents by Inventor Yunqiang Chen
Yunqiang Chen has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
-
Publication number: 20070189607Abstract: A method of automatically detecting features in an image includes: designing a gradient detection filter and a line detection filter; applying the gradient detection filter and line detection filter to detect structures in an image; and estimating feature dimensionality and orientation of the detected structures in the image. The computation cost of gradient detection and line detection when applied on an image is a constant number of operations independent of the size of the gradient and line detection filters.Type: ApplicationFiled: October 12, 2006Publication date: August 16, 2007Applicant: SIEMENS CORPORATE RESEARCH INCInventors: Yunqiang Chen, Tong Fang, Jason Tyan
-
Publication number: 20070147682Abstract: A method for processing image data includes inputting image data, determining a plurality of quadrature filter pairs based on filter parameter values to detect features of interest in the image data, applying the quadrature filter pairs to the image data to obtain a set of filter responses, and processing the filter responses to obtain the features of interest in the image data.Type: ApplicationFiled: December 4, 2006Publication date: June 28, 2007Applicant: SIEMENS CORPORATE RESEARCH, INC.Inventors: Ti-chiun Chang, Tong Fang, Jason Tyan, Yunqiang Chen
-
Publication number: 20070140407Abstract: Disclosed is a method and system for constructing, from a computerized tomography (CT) scan, an image relating to a physical structure. Projection data associated with the image is obtained and divided into a plurality of subsets. Filtered back projection (FBP) is then applied to each subset in the plurality of subsets. The image is constructed based on the application of the FBP to each subset in the plurality of subsets.Type: ApplicationFiled: October 9, 2006Publication date: June 21, 2007Applicant: SIEMENS CORPORATE RESEARCH INCInventors: Yunqiang Chen, Tong Fang
-
Publication number: 20070140582Abstract: A method for reducing noise in an image sequence includes: detecting structures in an image sequence; estimating lighting changes in the image sequence and compensating for the estimated lighting changes; detecting moving structures in the image sequence using the detected structures after compensating for the estimated lighting changes in the image sequence; and adaptively filtering imaging noise in the image sequence.Type: ApplicationFiled: October 6, 2006Publication date: June 21, 2007Applicant: SIEMENS CORPORATE RESEARCH INCInventors: Yunqiang Chen, Chunxiao Zhou, Tong Fang, Jason Tyan
-
Publication number: 20070133736Abstract: Certain exemplary embodiments comprise a method, which can comprise determining an image of a predetermined physiological structure of a patient. The image can be determined based upon a first set of image data of the predetermined physiological structure of the patient. The image can be based upon a second set of image data of the predetermined physiological structure of the patient. The image can be determined based upon an iteratively adjusted movement of the patient.Type: ApplicationFiled: October 12, 2006Publication date: June 14, 2007Applicant: SIEMENS CORPORATE RESEARCH INCInventors: Yunqiang Chen, Hao Wu, Tong Fang
-
Patent number: 7231064Abstract: A system and method for object tracking using probabilistic mode-based multi-hypothesis tracking (MHT) provides for robust and computationally efficient tracking of moving objects such as heads and faces in complex environments. A mode-based multi-hypothesis tracker uses modes that are local maximums which are refined from initial samples in a parametric state space. Because the modes are highly representative, the mode-based multi-hypothesis tracker effectively models non-linear probabilistic distributions using a small number of hypotheses. Real-time tracking performance is achieved by using a parametric causal contour model to refine initial contours to nearby modes. In addition, one common drawback of conventional MHT schemes, i.e., producing only maximum likelihood estimates instead of a desired posterior probability distribution, is addressed by introducing an importance sampling framework into MHT, and estimating the posterior probability distribution from the importance function.Type: GrantFiled: November 17, 2005Date of Patent: June 12, 2007Assignee: Microsoft CorporationInventors: Yong Rui, Yunqiang Chen
-
Patent number: 7171025Abstract: Automatic detection and tracking of multiple individuals includes receiving a frame of video and/or audio content and identifying a candidate area for a new face region in the frame. One or more hierarchical verification levels are used to verify whether a human face is in the candidate area, and an indication made that the candidate area includes a face if the one or more hierarchical verification levels verify that a human face is in the candidate area. A plurality of audio and/or video cues are used to track each verified face in the video content from frame to frame.Type: GrantFiled: January 25, 2005Date of Patent: January 30, 2007Assignee: Microsoft CorporationInventors: Yong Rui, Yunqiang Chen
-
Patent number: 7151843Abstract: Automatic detection and tracking of multiple individuals includes receiving a frame of video and/or audio content and identifying a candidate area for a new face region in the frame. One or more hierarchical verification levels are used to verify whether a human face is in the candidate area, and an indication made that the candidate area includes a face if the one or more hierarchical verification levels verify that a human face is in the candidate area. A plurality of audio and/or video cues are used to track each verified face in the video content from frame to frame.Type: GrantFiled: January 25, 2005Date of Patent: December 19, 2006Assignee: Microsoft CorporationInventors: Yong Rui, Yunqiang Chen
-
Patent number: 7130446Abstract: Automatic detection and tracking of multiple individuals includes receiving a frame of video and/or audio content and identifying a candidate area for a new face region in the frame. One or more hierarchical verification levels are used to verify whether a human face is in the candidate area, and an indication made that the candidate area includes a face if the one or more hierarchical verification levels verify that a human face is in the candidate area. A plurality of audio and/or video cues are used to track each verified face in the video content from frame to frame.Type: GrantFiled: December 3, 2001Date of Patent: October 31, 2006Assignee: Microsoft CorporationInventors: Yong Rui, Yunqiang Chen
-
Publication number: 20060173874Abstract: A method for interactively optimizing a system comprises interactively adjusting controlling parameters in a parameter set, by deriving successive pluralities of parameter sets in a parameter space, each of whose respective member parameter sets are respectively ranked in order, utilizing a ranking input based on respective system performance associated with each parameter set and from each of which plurality of parameter sets an optimal parameter set is selected and used as a point of departure for deriving the next following plurality of parameter sets in the parameter space, in accordance with the preceding ranking, in conjunction with a step size and a step direction derived from the ranking, in accordance with multidimensional scaling (MDS).Type: ApplicationFiled: January 27, 2006Publication date: August 3, 2006Inventors: Yunqiang Chen, Jason Tyan
-
Publication number: 20060087703Abstract: A method for multiple image restoration includes receiving a plurality of images corrupted by noise, and initializing a reduced noise estimate of the plurality of images. The method further includes estimating a probability of distributions of noise around each pixel and the probability of the signal, estimating mutual information between noise on the plurality of images based on the probabilities of distributions of noise around each pixel and the joint distribution of noise, and updating each pixel within a search range to determine a restored image by reducing the mutual information between the noise on the plurality of images.Type: ApplicationFiled: October 17, 2005Publication date: April 27, 2006Inventors: Yunqiang Chen, Hongcheng Wang, Tong Fang, Jason Tyan
-
Patent number: 7035764Abstract: A system and process for tracking an object state over time using particle filter sensor fusion and a plurality of logical sensor modules is presented. This new fusion framework combines both the bottom-up and top-down approaches to sensor fusion to probabilistically fuse multiple sensing modalities. At the lower level, individual vision and audio trackers can be designed to generate effective proposals for the fuser. At the higher level, the fuser performs reliable tracking by verifying hypotheses over multiple likelihood models from multiple cues. Different from the traditional fusion algorithms, the present framework is a closed-loop system where the fuser and trackers coordinate their tracking information. Furthermore, to handle non-stationary situations, the present framework evaluates the performance of the individual trackers and dynamically updates their object states.Type: GrantFiled: November 10, 2004Date of Patent: April 25, 2006Assignee: Microsoft CorporationInventors: Yong Rui, Yunqiang Chen
-
Publication number: 20060078163Abstract: A system and method for object tracking using probabilistic mode-based multi-hypothesis tracking (MHT) provides for robust and computationally efficient tracking of moving objects such as heads and faces in complex environments. A mode-based multi-hypothesis tracker uses modes that are local maximums which are refined from initial samples in a parametric state space. Because the modes are highly representative, the mode-based multi-hypothesis tracker effectively models non-linear probabilistic distributions using a small number of hypotheses. Real-time tracking performance is achieved by using a parametric causal contour model to refine initial contours to nearby modes. In addition, one common drawback of conventional MHT schemes, i.e., producing only maximum likelihood estimates instead of a desired posterior probability distribution, is addressed by introducing an importance sampling framework into MHT, and estimating the posterior probability distribution from the importance function.Type: ApplicationFiled: November 17, 2005Publication date: April 13, 2006Applicant: Microsoft CorporationInventors: Yong Rui, Yunqiang Chen
-
Publication number: 20060078181Abstract: A method and system for improving image quality by compounding a plurality of images to mitigate the effects of image noise. The method utilizes the independency between noise components for multiple image compounding. An effective measurement is designed to regularize the independency between noise in a traditional generative model based filtering framework, thereby enabling a more robust algorithmic solution to inaccurate signal/noise modeling. The method generally comprises selecting a plurality of images, calculating the residual error on each image; calculating the noise likelihood of each image, calculating the signal likelihood of the image, performing an independence analysis to regularize an independence constraint between the residual errors of the images, and summing the signal likelihood, noise likelihood and pairwise independency to approximate the joint independency between the residual errors.Type: ApplicationFiled: September 16, 2005Publication date: April 13, 2006Inventors: Yunqiang Chen, Hongcheng Wang, Tong Fang, Jason Tyan
-
Publication number: 20060072844Abstract: A gradient-based image enhancement and restoration method and system which applies an orientation-isotropy adaptive filter to the gradients of high structured regions, and directly suppresses the gradients in the noise or texture regions. A new gradient field is obtained from which image reconstruction can progress using least mean squares. The method generally comprises: inputting image data; calculating image gradients; defining the gradients as having large or small coherence; filtering the large coherence gradients for edge enhancement; suppressing the small coherence gradients for noise reduction; assembling an enhanced gradient field from the filtered large coherence and suppressed small coherence gradients; and optimizing the assembled gradient field into a restored image.Type: ApplicationFiled: September 20, 2005Publication date: April 6, 2006Inventors: Hongcheng Wang, Yunqiang Chen, Tong Fang, Jason Tyan
-
Patent number: 6999599Abstract: A system and method for object tracking using probabilistic mode-based multi-hypothesis tracking (MHT) provides for robust and computationally efficient tracking of moving objects such as heads and faces in complex environments. A mode-based multi-hypothesis tracker uses modes that are local maximums which are refined from initial samples in a parametric state space. Because the modes are highly representative, the mode-based multi-hypothesis tracker effectively models non-linear probabilistic distributions using a small number of hypotheses. Real-time tracking performance is achieved by using a parametric causal contour model to refine initial contours to nearby modes. In addition, one common drawback of conventional MHT schemes, i.e., producing only maximum likelihood estimates instead of a desired posterior probability distribution, is addressed by introducing an importance sampling framework into MHT, and estimating the posterior probability distribution from the importance function.Type: GrantFiled: June 7, 2002Date of Patent: February 14, 2006Assignee: Microsoft CorporationInventors: Yong Rui, Yunqiang Chen
-
Publication number: 20050210103Abstract: Automatic detection and tracking of multiple individuals includes receiving a frame of video and/or audio content and identifying a candidate area for a new face region in the frame. One or more hierarchical verification levels are used to verify whether a human face is in the candidate area, and an indication made that the candidate area includes a face if the one or more hierarchical verification levels verify that a human face is in the candidate area. A plurality of audio and/or video cues are used to track each verified face in the video content from frame to frame.Type: ApplicationFiled: January 25, 2005Publication date: September 22, 2005Applicant: Microsoft CorporationInventors: Yong Rui, Yunqiang Chen
-
Publication number: 20050188013Abstract: Automatic detection and tracking of multiple individuals includes receiving a frame of video and/or audio content and identifying a candidate area for a new face region in the frame. One or more hierarchical verification levels are used to verify whether a human face is in the candidate area, and an indication made that the candidate area includes a face if the one or more hierarchical verification levels verify that a human face is in the candidate area. A plurality of audio and/or video cues are used to track each verified face in the video content from frame to frame.Type: ApplicationFiled: January 25, 2005Publication date: August 25, 2005Applicant: Microsoft CorporationInventors: Yong Rui, Yunqiang Chen
-
Publication number: 20050129278Abstract: Automatic detection and tracking of multiple individuals includes receiving a frame of video and/or audio content and identifying a candidate area for a new face region in the frame. One or more hierarchical verification levels are used to verify whether a human face is in the candidate area, and an indication made that the candidate area includes a face if the one or more hierarchical verification levels verify that a human face is in the candidate area. A plurality of audio and/or video cues are used to track each verified face in the video content from frame to frame.Type: ApplicationFiled: January 25, 2005Publication date: June 16, 2005Applicant: Microsoft CorporationInventors: Yong Rui, Yunqiang Chen
-
Publication number: 20050114079Abstract: A system and process for tracking an object state over time using particle filter sensor fusion and a plurality of logical sensor modules is presented. This new fusion framework combines both the bottom-up and top-down approaches to sensor fusion to probabilistically fuse multiple sensing modalities. At the lower level, individual vision and audio trackers can be designed to generate effective proposals for the fuser. At the higher level, the fuser performs reliable tracking by verifying hypotheses over multiple likelihood models from multiple cues. Different from the traditional fusion algorithms, the present framework is a closed-loop system where the fuser and trackers coordinate their tracking information. Furthermore, to handle non-stationary situations, the present framework evaluates the performance of the individual trackers and dynamically updates their object states.Type: ApplicationFiled: November 10, 2004Publication date: May 26, 2005Applicant: Microsoft CorporationInventors: Yong Rui, Yunqiang Chen