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公开(公告)号：JP2010262653A
公开(公告)日：2010-11-18
申请号：JP2010102964
申请日：2010-04-28
Applicant: Internatl Business Mach Corp
, インターナショナル・ビジネス・マシーンズ・コーポレーションInternational Business Maschines Corporation Inventor： SHARATHCHANDRA UMAPATHIRAO PANKANTI , CONNELL JONATHAN HUDSON II , HAAS NORMAN , HAMPAPUR ARUN , PATNAIK YASHODHARA M , FLICKNER MAYRON DALE
IPC: G06Q50/00
CPC classification number: G07G1/12 , G07G1/0018 , G07G3/00
Abstract: PROBLEM TO BE SOLVED: To provide visual security for POS terminals. SOLUTION: Items 12 to be purchased is scanned by a store assistant using a barcode reader 16 attached to or positioned near the checkout station. When the items are scanned, they are identified based on the barcodes 14, and added to an item list. Item verification can then be performed at checkout using imaging technology. Specifically, when the items are scanned, an item verification unit 18 captures an appearance thereof. Item verification software 22 within the item verification unit accesses a database that associates items with their images/appearances. The appearance is compared for consistency to the identity as determined based on the scan. The item verification unit is a separate unit from a cash register, but functions in cooperation therewith. COPYRIGHT: (C)2011,JPO&INPIT
Abstract translation: 要解决的问题：为POS终端提供视觉安全。
解决方案：要购买的商品12由商店助理使用连接到或位于结帐台附近的条形码阅读器16进行扫描。 当物品被扫描时，它们基于条形码14被识别，并被添加到项目列表中。 然后可以使用成像技术在结帐时执行项目验证。 具体来说，当物品被扫描时，物品验证单元18捕获其外观。 项目验证单元内的项目验证软件22访问将项目与其图像/外观相关联的数据库。 将外观与基于扫描确定的身份的一致性进行比较。 物品验证单元是与收银机分开的单元，但与其配合起作用。 版权所有（C）2011，JPO＆INPIT
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公开(公告)号：GB2547752B
公开(公告)日：2018-01-24
申请号：GB201621726
申请日：2016-12-20
Applicant: IBM
Inventor： SHARATHCHANDRA UMAPATHIRAO PANKANTI , ARVIND KUMAR , JANUSZ MARECKI , BAN KAWAS
IPC: G06T7/70
Abstract: A method of operating an image detection device includes receiving an image, dividing the image into a plurality of patches, grouping ones of the plurality of patches, generating a set of saccadic paths through the plurality of patches of the image, generating a cluster-direction sequence for each saccadic path, generating a policy function for identifying an object in a new image using a combination of the cluster-direction sequences, and operating the image detection device using the policy function to identify an object in the new image.
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公开(公告)号：GB2588547A
公开(公告)日：2021-04-28
申请号：GB202019263
申请日：2019-05-13
Applicant: IBM
IPC: G06F17/00
Abstract: Generating a textual description of an image includes classifying an image represented by image data into a domain-specific category, and segmenting one or more elements in the image data based on the domain-specific category. Each element of the one or more elements is compared to a domain-independent model to detect one or more statistical anomalies in the one or more elements. The one or more detected statistical anomalies are characterized using one or more domain-independent text phrases. The one or more domain-independent text phrases are converted to one or more domain-specific descriptions based upon the domain-specific category.
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Patent Agency Ranking
公开(公告)号：GB2575607A
公开(公告)日：2020-01-15
申请号：GB201916128
申请日：2017-12-20
Applicant: IBM
Inventor： NALINI RATHA , KOMMINIST WELDEMARIAM , SHELBY SOLOMAN DARNELL , SHARATHCHANDRA UMAPATHIRAO PANKANTI
Abstract: A computer-implemented method modifies physical classroom resources in a classroom. One or more processors identify and quantify physical classroom resources in the classroom based on sensor readings received from sensors in a classroom. The processors determine physical classroom resource constraints that impede learning by students in the classroom based on the sensor readings from the sensors in the classroom. The processors detect one or more of the physical classroom resource constraints in the physical classroom resources identified by the sensor readings, and then adjust the one or more physical classroom resources based on the one or more detected physical classroom resource constraints.
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公开(公告)号：GB2547752A
公开(公告)日：2017-08-30
申请号：GB201621726
申请日：2016-12-20
Applicant: IBM
Inventor： SHARATHCHANDRA UMAPATHIRAO PANKANTI , ARVIND KUMAR , JANUSZ MARECKI , BAN KAWAS
IPC: G06T7/70
Abstract: A received image (1301) is divided into patches, which may have different sizes. A cluster-direction sequence (see fig. 6) is generated (1302) for each of a plurality of saccadic paths along the patches, the paths being given by a policy matrix (see figs. 8 & 9). The sequences are used to identify an object in the image. Path sequence generation using the matrix may comprise assigning (1303) a likelihood (which may be weighted (1304) using a total frequency of occurrence of the sequence in the matrix for a given class) that the image belongs to each class defined in the matrix, and identifying (1305) the object using a likelihood average over the sequences. Image context, e.g. previous observations or goal, may be used. The patches may be clustered into groups, e.g. using k-means clustering algorithm (see figs. 4&5). Specific salient features in an image may thus be identified, leading to a classification of the image by judging whether the salient features can identify a unique class of object (e.g. 9 MNIST digits, or image classes in ImageNet, e.g. cats, planes etc.) in the image with high probability. Classification may occur through progressive exclusion of other classes.
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公开(公告)号：GB2496547B
公开(公告)日：2017-05-31
申请号：GB201302244
申请日：2011-07-06
Applicant: IBM
Inventor： LEI DING , QUANFU FAN , SHARATHCHANDRA UMAPATHIRAO PANKANTI
IPC: G06K9/00 , G08B13/196
Abstract: Automated analysis of video data for determination of human behavior includes segmenting a video stream into a plurality of discrete individual frame image primitives which are combined into a visual event that may encompass an activity of concern as a function of a hypothesis. The visual event is optimized by setting a binary variable to true or false as a function of one or more constraints. The visual event is processed in view of associated non-video transaction data and the binary variable by associating the visual event with a logged transaction if associable, issuing an alert if the binary variable is true and the visual event is not associable with the logged transaction, and dropping the visual event if the binary variable is false and the visual event is not associable.
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公开(公告)号：GB2500839B
公开(公告)日：2017-04-05
申请号：GB201311821
申请日：2011-12-15
Applicant: IBM
Inventor： SHARATHCHANDRA UMAPATHIRAO PANKANTI , ARUN HAMPAPUR , JUN LI , CHARLES OTTO
Abstract: A system and computer program product for performing visual surveillance of one or more moving objects include registering one or more images captured by one or more cameras, wherein registering the one or more images comprises region-based registration of the one or more images in two or more adjacent frames, performing motion segmentation of the one or more images to detect one or more moving objects and one or more background regions in the one or more images, and tracking the one or more moving objects to facilitate visual surveillance of the one or more moving objects.
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公开(公告)号：GB2508094B
公开(公告)日：2016-05-25
申请号：GB201318865
申请日：2012-04-13
Applicant: IBM
Inventor： ANKUR DATTA , ROGERIO SCHMIDT FERIS , SHARATHCHANDRA UMAPATHIRAO PANKANTI , BEHJAT SIDDIQUE , YUN ZHAI
Abstract: Training data object images are clustered as a function of motion direction attributes and resized from respective original into same aspect ratios. Motionlet detectors are learned for each of the sets from features extracted from the resized object blobs. A deformable sliding window is applied to detect an object blob in input by varying window size, shape or aspect ratio to conform to a shape of the detected input video object blob. A motion direction of an underlying image patch of the detected input video object blob is extracted and motionlet detectors selected and applied that have similar motion directions. An object is thus detected within the detected blob and semantic attributes of an underlying image patch extracted if a motionlet detectors fires, the extracted semantic attributes available for use for searching for the detected object.
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