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公开(公告)号：US10275641B2
公开(公告)日：2019-04-30
申请号：US15265094
申请日：2016-09-14
Applicant: INTELLI-VISION
Inventor： Chandan Gope , Gagan Gupta , Nitin Jindal , Amit Agarwal
Abstract: The present invention discloses methods and systems face recognition. Face recognition involves receiving an image/frame, detecting one or more faces in the image, detecting feature points for each of the detected faces in the image, aligning and normalizing the detected feature points, extracting feature descriptors based on the detected feature points and matching the extracted feature descriptors with a set of pre-stored images for face recognition.
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Patent Agency Ranking
2.发明申请公开(公告)号：US20170213080A1
公开(公告)日：2017-07-27
申请号：US15226555
申请日：2016-08-02
Applicant: INTELLI-VISION
Inventor： Vaidhi Nathan , Gagan Gupta , Nitin Jindal , Chandan Gope
CPC classification number: G06K9/00369 , G06K9/4642 , G06K9/6212 , G06T7/11
Abstract: The present invention discloses methods and systems for detecting a human body in an image using a machine learning model. The method includes selecting one or more candidate regions from one or more regions in an image based on a pre-defined threshold. Then, a body is detected in a candidate region of the one or more candidate regions, based on a set of pair-wise constraints. The body detection further includes detection of various body parts. Thereafter, a score is computed for each detected body part and a final score for the candidate region is computed, based on the scores of the detected body parts.
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公开(公告)号：US20170098119A1
公开(公告)日：2017-04-06
申请号：US15265094
申请日：2016-09-14
Applicant: INTELLI-VISION
Inventor： Chandan Gope , Gagan Gupta , Nitin Jindal , Amit Agarwal
CPC classification number: G06K9/00281 , G06K9/00288 , G06K9/4642 , G06K2009/4666
Abstract: The present invention discloses methods and systems face recognition. Face recognition involves receiving an image/frame, detecting one or more faces in the image, detecting feature points for each of the detected faces in the image, aligning and normalizing the detected feature points, extracting feature descriptors based on the detected feature points and matching the extracted feature descriptors with a set of pre-stored images for face recognition.
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公开(公告)号：US10169684B1
公开(公告)日：2019-01-01
申请号：US15179966
申请日：2016-06-10
Applicant: INTELLI-VISION
Inventor： Vaidhi Nathan , Gagan Gupta , Nitin Jindal , Chandan Gope
Abstract: The present invention discloses methods and systems for recognizing an object in an input image based on stored training images. An object recognition system the input image, computes a signature of the input image, compares the signature with one or more stored signatures and retrieves one or more matching images from the set of training images. The matching images are then displayed to the user for further action.
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5.发明申请公开(公告)号：US20170213081A1
公开(公告)日：2017-07-27
申请号：US15226610
申请日：2016-08-02
Applicant: INTELLI-VISION
Inventor： Vaidhi Nathan , Gagan Gupta , Nitin Jindal , Chandan Gope
IPC: G06K9/00
CPC classification number: G06K9/00369 , G06K9/4642 , G06K9/6212 , G06T7/11
Abstract: The present invention discloses methods and systems for detecting a human body in an image using a machine learning model. The method includes selecting one or more candidate regions from one or more regions in an image based on a pre-defined threshold. Then, a body is detected in a candidate region of the one or more candidate regions, based on a set of pair-wise constraints. The body detection further includes detection of various body parts. Thereafter, a score is computed for each detected body part and a final score for the candidate region is computed, based on the scores of the detected body parts.
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公开(公告)号：US20170300786A1
公开(公告)日：2017-10-19
申请号：US15265026
申请日：2016-09-14
Applicant: INTELLI-VISION
Inventor： Chandan Gope , Gagan Gupta , Nitin Jindal , Amit Agarwal
CPC classification number: G06K9/6267 , G06K9/00791 , G06K2209/01 , G06K2209/15 , G06T5/002 , G06T5/20
Abstract: The present invention discloses methods, systems and computer programmable products for detecting license plates and recognizing characters in the licence plates. The system receives an image and identifies one or more regions including a license plate. The one or more regions are converted into a plurality of binarized images, which are then filtered to remove noise. Next, one or more clusters of characters are identified in the plurality of binarized images. The one or more clusters of characters are analyzed to recognize a set of characters, wherein each character in the set includes a confidence value.
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