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公开(公告)号：US10748030B2
公开(公告)日：2020-08-18
申请号：US16307409
申请日：2017-10-12
发明人： Pranoy Hari , Shilpa Yadukumar Rao , Rajashree Ramakrishnan , Avishek Kumar Shaw , Archan Ray , Nishant Kumar , Dipti Prasad Mukherjee
摘要： Object recognition based estimation of planogram compliance provides an expected arrangement of products in shelves. Identifying whether a product is placed in an appropriate location of a shelf is a challenging task due to various real-time parameters associated with image capturing. In the present disclosure, an input image associated with shelf of a retail store is received and a product images are cropped. Further, a set of reference images stored in a database are scaled corresponding to the input image. Further, one or more composite matching scores are calculated based on normalized cross-correlation and shape based feature matching to obtain one or more probable product images associated with a location. Further, a Directed Acyclic Graph (DAG) is constructed based on the one or more composite scores and the one or more probable products. Finally, an optimal matching product image for a particular location is obtained from the DAG.
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2.发明授权公开(公告)号：US11354549B2
公开(公告)日：2022-06-07
申请号：US16928682
申请日：2020-07-14
发明人： Avishek Kumar Shaw , Rajashree Ramakrishnan , Shilpa Yadukumar Rao , Pranoy Hari , Dipti Prasad Mukherjee , Bikash Santra
摘要： This disclosure relates generally to a system and method to identify various products on a plurality of images of various shelves of a retail store to facilitate compliance with respect to planograms. Planogram is a visual plan, which designates the placement of products on shelves and merchandising display fixtures of a retail store. Planograms are used to create consistency between store locations, to provide proper shelf space allocation, to improve visual merchandising appeal, and to create product-pairing suggestions. There are a few assumptions considering one instance per product class is available beforehand and the physical dimension of each product template is available in some suitable unit of length. In case of absence of physical dimension of the products, a context information of the retail store will be used. The context information is that the products of similar shapes or classes are arranged together in the shelves for consumers' convenience.
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公开(公告)号：US09589203B2
公开(公告)日：2017-03-07
申请号：US14665345
申请日：2015-03-23
CPC分类号： G06K9/44 , G06F3/011 , G06K9/00342 , G06K9/4685
摘要： A processor implemented system and method for identification of an activity performed by a subject based on sensor data analysis is described herein. In an implementation, the method includes capturing movements of the subject in real-time using a sensing device. At least one action associated with the subject is ascertained from a predefined set of actions. From the predefined set of actions, a plurality of actions can collectively form at least one activity. The ascertaining is based on captured movements of the subject and at least one predefined action rule. The at least one action rule is based on context-free grammar (CFG) and is indicative of a sequence of actions for occurrence of the at least one activity. Further, a current activity performed by the subject is dynamically determined, based on the at least one action and an immediately preceding activity, using a non-deterministic push-down automata (NPDA) state machine.
摘要翻译： 本文描述了一种用于基于传感器数据分析来识别被摄体执行的活动的处理器实现的系统和方法。 在实现中，该方法包括使用感测装置实时地捕获被摄体的移动。 根据预定义的一组动作来确定与主题相关联的至少一个动作。 从预定义的一组动作，多个动作可以共同形成至少一个活动。 确定是基于被摄体的捕获的移动和至少一个预定义的动作规则。 所述至少一个动作规则基于上下文无关语法（CFG），并且指示用于发生所述至少一个活动的一系列动作。 此外，使用非确定性下推自动机（NPDA）状态机，基于所述至少一个动作和紧接在前的活动来动态地确定由所述对象执行的当前活动。
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公开(公告)号：US09430701B2
公开(公告)日：2016-08-30
申请号：US14614891
申请日：2015-02-05
CPC分类号： G06K9/00369 , G06K9/00201 , G06K9/00342 , G06K9/00771 , G06K9/40 , G06K9/4638 , G06K2009/485 , G06T2207/10024 , G06T2207/10028 , G06T2207/20021 , G06T2207/20072 , G06T2207/30196 , G06T2207/30232
摘要： Disclosed is a system and method for detecting a human in an image, and a corresponding activity. The image is captured, wherein the image comprises a plurality of pixels having gray scale information and a depth information. The image is segmented into a plurality of segments based upon the depth information. A connected component analysis is performed on a segment in order to segregate the one or more objects into noisy objects and candidate objects, the noisy objects are eliminated from the segment. A plurality of features are extracted from the candidate objects, and are evaluated using a Hidden Markov Model (HMM) model in order to determine the candidate objects as one of the human or non-human. The corresponding activity associated with the human is detected based on a depth value associated with each pixel corresponding to the candidate object in the image.
摘要翻译： 公开了一种用于检测图像中的人的系统和方法以及相应的活动。 捕获图像，其中图像包括具有灰度信息和深度信息的多个像素。 基于深度信息将图像分割成多个片段。 在段上执行连接分量分析，以便将一个或多个对象分离成噪声对象和候选对象，从该段中消除嘈杂对象。 从候选对象中提取多个特征，并且使用隐马尔可夫模型（HMM）模型来评估，以便将候选对象确定为人或非人之一。 基于与图像中的候选对象对应的每个像素相关联的深度值来检测与人相关联的相应活动。
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