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公开(公告)号:US10192087B2
公开(公告)日:2019-01-29
申请号:US15175997
申请日:2016-06-07
Applicant: Digimarc Corporation
Inventor: Bruce L. Davis , Tony F. Rodriguez , Geoffrey B. Rhoads , John D. Lord , Eric D. Evans , Rebecca L. Gerlach , Yang Bai , John Stach
IPC: G06K7/10 , G06K9/78 , G06Q30/00 , G06K7/14 , G06Q20/20 , G07G1/00 , G06K17/00 , G06F3/147 , G06Q10/08 , G06Q30/06
Abstract: In some arrangements, product packaging is digitally watermarked over most of its extent to facilitate high-throughput item identification at retail checkouts. Imagery captured by conventional or plenoptic cameras can be processed (e.g., by GPUs) to derive several different perspective-transformed views—further minimizing the need to manually reposition items for identification. Crinkles and other deformations in product packaging can be optically sensed, allowing such surfaces to be virtually flattened to aid identification. Piles of items can be 3D-modelled and virtually segmented into geometric primitives to aid identification, and to discover locations of obscured items. Other data (e.g., including data from sensors in aisles, shelves and carts, and gaze tracking for clues about visual saliency) can be used in assessing identification hypotheses about an item. A great variety of other features and arrangements are also detailed.
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公开(公告)号:US09922220B2
公开(公告)日:2018-03-20
申请号:US15176498
申请日:2016-06-08
Applicant: Digimarc Corporation
Inventor: Eric D. Evans , Tomas Filler
IPC: G06K9/00 , G06K7/10 , G06T5/00 , G06K7/14 , G06T3/00 , G06K9/18 , G06K9/36 , G06K9/62 , G06K9/46
CPC classification number: G06K7/10722 , G06K7/146 , G06K9/00 , G06K9/18 , G06K9/36 , G06K9/4676 , G06K9/6262 , G06K2009/363 , G06T3/00 , G06T5/002 , G06T2207/20081
Abstract: Object recognition by point-of-sale camera systems is aided by first removing perspective distortion. Yet pose of the object—relative to the system—depends on actions of the operator, and is usually unknown. Multiple trial counter-distortions to remove perspective distortion can be attempted, but the number of such trials is limited by the frame rate of the camera system—which limits the available processing interval. One embodiment of the present technology examines historical image data to determine counter-distortions that statistically yield best object recognition results. Similarly, the system can analyze historical data to learn what sub-parts of captured imagery most likely enable object recognition. A set-cover strategy is desirably used. In some arrangements, the system identifies different counter-distortions, and image sub-parts, that work best with different clerk- and customer-operators of the system, and processes captured imagery accordingly. A great variety of other features and arrangements are also detailed.
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公开(公告)号:US20160364634A1
公开(公告)日:2016-12-15
申请号:US15175997
申请日:2016-06-07
Applicant: Digimarc Corporation
Inventor: Bruce L. Davis , Tony F. Rodriguez , Geoffrey B. Rhoads , John D. Lord , Alastair M. Reed , Eric D. Evans , Rebecca L. Gerlach , Yang Bai , John Stach , Tomas Filler , Marc G. Footen , Sean Calhoon
CPC classification number: G06K9/78 , G06F3/147 , G06K7/10861 , G06K7/1456 , G06K2017/0051 , G06K2017/0093 , G06Q10/08 , G06Q10/087 , G06Q20/201 , G06Q20/208 , G06Q30/00 , G06Q30/0601 , G07G1/0045
Abstract: In some arrangements, product packaging is digitally watermarked over most of its extent to facilitate high-throughput item identification at retail checkouts. Imagery captured by conventional or plenoptic cameras can be processed (e.g., by GPUs) to derive several different perspective-transformed views—further minimizing the need to manually reposition items for identification. Crinkles and other deformations in product packaging can be optically sensed, allowing such surfaces to be virtually flattened to aid identification. Piles of items can be 3D-modelled and virtually segmented into geometric primitives to aid identification, and to discover locations of obscured items. Other data (e.g., including data from sensors in aisles, shelves and carts, and gaze tracking for clues about visual saliency) can be used in assessing identification hypotheses about an item. A great variety of other features and arrangements are also detailed.
Abstract translation: 在一些安排中,产品包装在其大部分程度上以数字水印方式,以促进零售结算处的高通量物品识别。 可以通过传统或全光照相机拍摄的图像(例如,通过GPU)来处理几个不同的透视变换视图 - 进一步最小化手动重新定位项目以进行识别的需要。 产品包装中的皱纹和其他变形可以光学感测,允许这些表面几乎变平,以帮助识别。 物品堆可以3D建模,并将其虚拟分割成几何图元,以帮助识别,并发现隐藏物品的位置。 可以使用其他数据(例如,包括来自在通道中的传感器的数据,架子和推车以及关于视觉显着性的线索的凝视跟踪)来评估关于物品的识别假设。 还详细介绍了各种各样的其他功能和安排。
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公开(公告)号:US20160110839A1
公开(公告)日:2016-04-21
申请号:US14978827
申请日:2015-12-22
Applicant: Digimarc Corporation
Inventor: Yang Bai , Eric D. Evans , Tomas Filler
CPC classification number: G06T1/005 , G06K9/2054 , G06K9/3233 , G06T7/10 , G06T7/194 , G06T7/73 , G06T2201/0051 , G06T2201/0065
Abstract: In some arrangements, product packaging is digitally watermarked over most of its extent to facilitate high-throughput item identification at retail checkouts. Imagery of such packaging is analyzed to detect digital watermarking. One claim recites a method utilized at a retail checkout location comprising: receiving imagery representing a packaged item from a digital camera, the packaged item including digital watermarking hidden on its packaging, the packaged item moving relative to the digital camera; determining a region in the imagery corresponding to at least one relatively faster moving object; arranging watermark detection blocks over the determine region; an detecting the digital watermarking from the watermark detection blocks. Of course other claims and combinations are also provided.
Abstract translation: 在一些安排中,产品包装在其大部分程度上以数字水印方式,以促进零售结算处的高通量物品识别。 分析这种包装的图像以检测数字水印。 一个权利要求记载了在零售结帐地点使用的方法,包括:从数字照相机接收表示包装物品的图像,所述包装物品包括隐藏在其包装上的数字水印,所述包装物品相对于所述数码相机移动; 确定对应于至少一个相对较快的移动物体的图像中的区域; 在确定区域上布置水印检测块; 从水印检测块检测数字水印。 当然,也提供其他权利要求和组合。
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公开(公告)号:US20130311329A1
公开(公告)日:2013-11-21
申请号:US13860834
申请日:2013-04-11
Applicant: Digimarc Corporation
Inventor: Edward B. Knudson , Eric D. Evans , Ashleigh A. Newell , Tony F. Rodriguez , Carrie M. Sutton , Matthew M. Weaver , William Y. Conwell , Donald Haaga
CPC classification number: G06Q50/01 , G06F16/50 , G06K9/228 , G06K9/3241 , G06Q30/0639
Abstract: In one aspect, a user captures an image of a physical object (e.g., of a grocery item, using a smartphone). The depicted object is identified, such as by extracting fingerprint or watermark data from the imagery. Other imagery depicting that object—or depicting related objects—is identified on the web, and is displayed to the user on the smartphone screen. The user may select one or more of these images and direct that they be posted to a social network account (e.g., Pinterest) associated with the user. In another aspect, the user's location is sensed (e.g., an aisle of a department store), and a collection of images depicting nearby products is presented to the user for selection and posting to a social networking service. A great variety of other features and arrangements are also detailed.
Abstract translation: 在一个方面,用户捕获物理对象(例如,使用智能电话的杂货项目)的图像。 所描绘的对象被识别,例如通过从图像提取指纹或水印数据。 描绘该对象或描绘相关对象的其他图像在网络上被识别,并在智能手机屏幕上显示给用户。 用户可以选择这些图像中的一个或多个,并指示它们被发布到与用户相关联的社交网络帐户(例如,Pinterest)。 在另一方面,感测用户的位置(例如,百货公司的通道),并且向用户呈现描绘附近产品的图像的集合以供选择并发布到社交网络服务。 还详细介绍了各种各样的其他功能和安排。
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公开(公告)号:US20130223673A1
公开(公告)日:2013-08-29
申请号:US13750752
申请日:2013-01-25
Applicant: Digimarc Corporation
Inventor: Bruce L. Davis , Tony F. Rodriguez , Geoffrey B. Rhoads , John D. Lord , Alastair M. Reed , Eric D. Evans , Rebecca L. Gerlach , Yang Bai , John Stach , Tomas Filler , Marc G. Footen , Sean Calhoon
CPC classification number: G06K9/78 , G06F3/147 , G06K7/10861 , G06K7/1456 , G06K2017/0051 , G06K2017/0093 , G06Q10/08 , G06Q10/087 , G06Q20/201 , G06Q20/208 , G06Q30/00 , G06Q30/0601 , G07G1/0045
Abstract: In some arrangements, product packaging is digitally watermarked over most of its extent to facilitate high-throughput item identification at retail checkouts. Imagery captured by conventional or plenoptic cameras can be processed (e.g., by GPUs) to derive several different perspective-transformed views—further minimizing the need to manually reposition items for identification. Crinkles and other deformations in product packaging can be optically sensed, allowing such surfaces to be virtually flattened to aid identification. Piles of items can be 3D-modelled and virtually segmented into geometric primitives to aid identification, and to discover locations of obscured items. Other data (e.g., including data from sensors in aisles, shelves and carts, and gaze tracking for clues about visual saliency) can be used in assessing identification hypotheses about an item. A great variety of other features and arrangements are also detailed.
Abstract translation: 在一些安排中,产品包装在其大部分程度上以数字水印方式,以促进零售结算处的高通量物品识别。 可以通过传统或全光照相机拍摄的图像(例如,通过GPU)来处理几个不同的透视变换视图 - 进一步最小化手动重新定位项目以进行识别的需要。 产品包装中的皱纹和其他变形可以光学感测,允许这些表面几乎变平,以帮助识别。 物品堆可以3D建模,并将其虚拟分割成几何图元,以帮助识别,并发现隐藏物品的位置。 可以使用其他数据(例如,包括来自在通道中的传感器的数据,架子和推车以及关于视觉显着性的线索的凝视跟踪)来评估关于物品的识别假设。 还详细介绍了各种各样的其他功能和安排。
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