公开(公告)号：US20170154204A1

公开(公告)日：2017-06-01

申请号：US14956249

申请日：2015-12-01

Applicant: INTEL CORPORATION

Inventor： WOOJU RYU ,  TAE-HOON KIM ,  MINJE PARK ,  BOOGEON YOON ,  JINWOOK LEE

IPC: G06K9/00 ,  G06T1/20 ,  G06T7/00 ,  G06K9/46 ,  G06K9/48

CPC classification number: G06K9/00208 ,  G06K9/00214 ,  G06K9/4604 ,  G06K9/4676 ,  G06K9/481 ,  G06K9/6211 ,  G06T7/0061 ,  G06T7/149

Abstract: A system, article, and method of curved object recognition using image matching for image processing.

公开(公告)号：US20170256086A1

公开(公告)日：2017-09-07

申请号：US15124811

申请日：2015-12-18

Applicant: INTEL CORPORATION

Inventor： MINJE PARK ,  TAE-HOON KIM ,  MYUNG-HO JU ,  JIHYEON YI ,  XIAOLU SHEN ,  LIDAN ZHANG ,  QIANG LI

IPC: G06T13/40 ,  G06T7/73

CPC classification number: G06T13/40 ,  G06T7/73 ,  G06T17/20 ,  G06T2207/20084 ,  G06T2207/30201 ,  G06T2210/44

Abstract: Avatar animation systems disclosed herein provide high quality, real-time avatar animation that is based on the varying countenance of a human face. In some example embodiments, the real-time provision of high quality avatar animation is enabled at least in part, by a multi-frame regressor that is configured to map information descriptive of facial expressions depicted in two or more images to information descriptive of a single avatar blend shape. The two or more images may be temporally sequential images. This multi-frame regressor implements a machine learning component that generates the high quality avatar animation from information descriptive of a subject's face and/or information descriptive of avatar animation frames previously generated by the multi-frame regressor. The machine learning component may be trained using a set of training images that depict human facial expressions and avatar animation authored by professional animators to reflect facial expressions depicted in the set of training images.

公开(公告)号：US20160140391A1

公开(公告)日：2016-05-19

申请号：US14541631

申请日：2014-11-14

Applicant: Intel Corporation

Inventor： TAE-HOON KIM ,  MINJE PARK

IPC: G06K9/00 ,  H04N7/18 ,  G06K9/62 ,  G06K9/46 ,  G06T7/20

CPC classification number: G06K9/00624 ,  G06K9/3241 ,  G06K9/46 ,  G06K9/6201 ,  G06K2009/3291 ,  G06T7/20 ,  H04N5/232 ,  H04N7/18

Abstract: Techniques related to automatic target object selection from multiple tracked objects for imaging devices are discussed. Such techniques may include generating one or more object selection metrics such as accumulated distances from frame center, accumulated velocities, and trajectory comparisons of predicted to actual trajectories for tracked objects and selecting the target object based on the object selection metric or metrics.

Abstract translation: 讨论了与用于成像设备的多个跟踪对象的自动目标对象选择相关的技术。 这样的技术可以包括生成一个或多个对象选择度量，例如来自帧中心的累积距离，累积速度，以及针对跟踪对象的预测到实际轨迹的轨迹比较，以及基于对象选择度量或度量来选择目标对象。

公开(公告)号：US20160171344A1

公开(公告)日：2016-06-16

申请号：US14567147

申请日：2014-12-11

Applicant: INTEL CORPORATION

Inventor： KE CHEN ,  BONGJIN JUN ,  YI-JEN CHIU ,  TAE-HOON KIM ,  DUKHWAN KIM

IPC: G06K9/62 ,  H04N19/90

CPC classification number: G06K9/6267 ,  G06K9/00228 ,  G06K9/4609 ,  G06K9/6203 ,  G06K9/6257 ,  G06K2009/4666 ,  H04N19/90

Abstract: Techniques related to object detection using binary coded images are discussed. Such techniques may include performing object detection based on multiple spatial correlation mappings between a generated binary coded image and a binary coded image based object detection model and nesting look up tables such that binary coded representations are grouped and such groups are associated with confidence values for performing object detection.

Abstract translation: 讨论与使用二进制编码图像的对象检测相关的技术。 这样的技术可以包括基于生成的二进制编码图像和基于二进制编码图像的对象检测模型和嵌套查找表之间的多个空间相关性映射执行对象检测，使得二进制编码表示被分组，并且这些组与用于执行的置信度值相关联 物体检测。

公开(公告)号：US20160140394A1

公开(公告)日：2016-05-19

申请号：US14541981

申请日：2014-11-14

Applicant: Intel Corporation

Inventor： JINWOOK LEE ,  YONGCHAN PARK ,  HONGMO JE ,  TAE-HOON KIM

IPC: G06K9/00 ,  G06K9/46

CPC classification number: G06K9/00711 ,  G06K9/4642 ,  G06K9/4652 ,  G06T7/246

Abstract: System, apparatus, method, and computer readable media for on-the-fly captured image data object tracking. An image or video stream is processed to detect and track an object in concurrence with generation of the stream by a camera module. In one exemplary embodiment, HD image frames are processed at a rate of 30 fps, or more, to track one or more target object. In embodiments, object detection is validated prior to employing detected object descriptor(s) as learning data to generate or update an object model. A device platform including a camera module and comporting with the exemplary architecture may provide 3A functions based on objects robustly tracked in accordance with embodiments.

Abstract translation: 系统，装置，方法和计算机可读介质，用于即时拍摄的图像数据对象跟踪。 处理图像或视频流，以便通过相机模块生成流来检测和跟踪对象。 在一个示例性实施例中，以30fps或更大的速率处理HD图像帧以跟踪一个或多个目标对象。 在实施例中，在使用检测到的对象描述符作为学习数据来生成或更新对象模型之前，对对象检测进行验证。 包括相机模块和与示例性体系结构对比的设备平台可以提供基于根据实施例坚固地跟踪的对象的3A功能。