公开(公告)号：US20210390789A1

公开(公告)日：2021-12-16

申请号：US17109045

申请日：2020-12-01

Applicant: QUALCOMM Incorporated

Inventor： Peng LIU ,  Lei WANG ,  Zhen WANG ,  Ke-Li CHENG ,  Ning BI

IPC: G06T19/20 ,  G06K9/00 ,  G06T17/20 ,  G06T7/70 ,  G06T7/50 ,  G06T11/00 ,  G06K9/62

Abstract: Systems and techniques are provided for facial image augmentation. An example method can include obtaining a first image capturing a face. Using the first image, the method can determine, using a prediction model, a UV face position map including a two-dimensional (2D) representation of a three-dimensional (3D) structure of the face. The method can generate, based on the UV face position map, a 3D model of the face. The method can generate an extended 3D model of the face by extending the 3D model to include region(s) beyond a boundary of the 3D model. The region(s) can include a forehead region, a region surrounding at least a portion of the face, and/or other region. The method can generate, based on the extended 3D model, a second image depicting the face in a rotated position relative to a position of the face in the first image.

公开(公告)号：US20190114804A1

公开(公告)日：2019-04-18

申请号：US15966396

申请日：2018-04-30

Applicant: QUALCOMM Incorporated

Inventor： Sairam SUNDARESAN ,  Mithun Kumar RANGANATH ,  Matthew FISCHLER ,  Ning BI

IPC: G06T7/73 ,  G06K9/66 ,  G06K9/62 ,  G06K9/00

Abstract: Techniques and systems are provided for tracking objects in one or more images. For example, a trained network can be applied to a first image of a sequence of images to detect one or more objects in the first image. The trained network can be applied to less than all images of the sequence of images. A second image of the sequence of images and a detection result from application of the trained network to the first image are obtained. The detection result includes the detected one or more objects from the first image. A first object tracker can be applied to the second image using the detection result from application of the trained network to the first image. Applying the first object tracker can include adjusting one or more locations of one or more bounding boxes associated with the detected one or more objects in the second image to track the detected one or more objects in the second image. A second object tracker can also be applied to the second image to track at least one object of the detected one or more objects in the second image. The second object tracker is applied to more images of the sequence of images than the trained network and the first object tracker. Object tracking can be performed for the second image based on application of the first object tracker and the second object tracker.

公开(公告)号：US20180341813A1

公开(公告)日：2018-11-29

申请号：US15973114

申请日：2018-05-07

Applicant: QUALCOMM Incorporated

Inventor： Ying CHEN ,  Yang ZHOU ,  Ning BI

IPC: G06K9/00 ,  G06T7/246 ,  G06T7/90 ,  G06K9/46 ,  G06T7/50 ,  G06K9/03 ,  G06T7/194

CPC classification number: G06K9/00744 ,  G06K9/00758 ,  G06K9/00771 ,  G06K9/03 ,  G06K9/4647 ,  G06T7/194 ,  G06T7/251 ,  G06T7/50 ,  G06T7/90 ,  G06T2207/10016 ,  G06T2207/20121

Abstract: Techniques and systems are provided for maintaining blob trackers for one or more video frames. For example, a blob tracker is identified for a current video frame. The blob tracker is associated with a blob detected for the current video frame. The blob includes pixels of at least a portion of one or more objects in the current video frame. A current characteristic of pixels in a region of the current video frame associated with the blob tracker is determined. A previous characteristic of pixels in a region of a previous video frame associated with the blob tracker is also determined. A difference is determined between the current characteristic and the previous characteristic, and a status of the blob tracker is determined based on the determined difference. The status of the blob tracker indicating whether to maintain the blob tracker for the one or more video frames.