公开(公告)号：US08965123B2

公开(公告)日：2015-02-24

申请号：US13849588

申请日：2013-03-25

Applicant: Tata Consultancy Services Limited ,  Indian Statistical Institute

Inventor： Tanushyam Chattopadhyay ,  Ujjwal Bhattacharya ,  Bidyut Baran Chaudhuri

IPC: G06K9/00 ,  G06K9/34 ,  G06K9/38

CPC classification number: G06K9/344 ,  G06K9/38 ,  G06K2209/01

Abstract: A system and a method for identification of alphanumeric characters present in a series in an image are disclosed. The system and method captures the image and further processes it for binarization by computing a pattern of the image. The generated binarized images are then filtered for removing unwanted components. Candidate images are identified out of the filtered binarized images. All the obtained candidate images are combined to generate a final candidate image which is further segmented in order to recognize a valid alphanumeric character present in the series.

Abstract translation: 公开了用于识别图像中的一系列中的字母数字字符的系统和方法。 系统和方法捕获图像，并通过计算图像的图案进一步处理它进行二值化。 然后过滤生成的二进制化图像以除去不需要的组件。 从已滤波的二值化图像中识别候选图像。 所有获得的候选图像被组合以产生进一步分段的最终候选图像，以便识别该系列中存在的有效字母数字字符。

公开(公告)号：US20140351790A1

公开(公告)日：2014-11-27

申请号：US14286068

申请日：2014-05-23

Applicant: TATA CONSULTANCY SERVICES LIMITED

Inventor： Avik Ghose ,  Arpan Pal ,  Anirban Dutta Choudhury ,  Tanushyam Chattopadhyay ,  Plaban Kumar Bhowmick ,  Dhiman Chattopadhyay

IPC: G06F9/44 ,  G06F17/30

CPC classification number: G06F8/70 ,  G06F8/36 ,  G06F16/2228

Abstract: An application development system for development of Internet of Things (IoT) application includes a cataloging module to obtain an input from an application developer. The input comprises data related to the IoT application to be developed. The cataloging module further retrieves a plurality of reusable artefacts from a knowledge database based on the input. A recommendation module in the application development system recommends, to the application developer, artefacts from amongst the plurality of reusable artefacts, based at least on one of a feedback associated with each of the plurality of reusable artefacts, an expert analysis, and a combination of the expert analysis and the feedback. An association module in the application development system associates artefacts selected by the application developer with each other for development of the IoT application.

Abstract translation: 物联网应用开发系统（IoT）应用程序包括编目模块，用于从应用程序开发人员获取输入。 该输入包括与要开发的IoT应用有关的数据。 编目模块基于输入进一步从知识数据库检索多个可重用的伪像。 所述应用开发系统中的推荐模块至少基于与所述多个可重复使用的人工制品中的每一个相关联的反馈中的一个，专家分析以及所述多个可重复使用的人工制品的组合中的至少一个，向所述应用开发者推荐所述多个可再利用人造物中的人造物 专家分析和反馈。 应用程序开发系统中的关联模块将由应用程序开发人员选择的伪装相互关联，以便开发IoT应用程序。

公开(公告)号：US11906958B2

公开(公告)日：2024-02-20

申请号：US17366777

申请日：2021-07-02

Applicant: Tata Consultancy Services Limited

Inventor： Tanushyam Chattopadhyay ,  Abhisek Das ,  Suvra Dutta ,  Shubhrangshu Ghosh ,  Prateep Misra

IPC: G05B23/02 ,  G06F18/20 ,  G06F18/2415

CPC classification number: G05B23/0227 ,  G06F18/2415 ,  G06F18/285

Abstract: State-of-the-art approaches have concentrated on building solution(s) to match the amplitude of a time series with a user given one. However, these have failed to implement solution(s) which enables searching for pattern(s) that can depict human vision psychology. Embodiments of the present disclosure determine occurrence of pattern of interest in time series data for anomaly detection, wherein time series data is obtained, and first order derivative is computed. Further an angle of change in direction is derived based on a gradient of change in value of the time series data. This angle is further converted to a measurement unit. The time series data is quantized into bins and a weighted finite state transducers diagram (WFSTD) is obtained based on domain knowledge which is then converted to specific pattern. The specific pattern is searched in the bins to determine occurrence/count of the specific pattern for anomaly detection.

公开(公告)号：US11586928B2

公开(公告)日：2023-02-21

申请号：US16265906

申请日：2019-02-01

Applicant: Tata Consultancy Services Limited

Inventor： Tulika Bose ,  Angshul Majumdar ,  Tanushyam Chattopadhyay

IPC: G06N3/04 ,  G06N3/08 ,  H04L45/50

Abstract: A method and system for incorporating regression into a Stacked Auto Encoder utilizing deep learning based regression technique that enables joint learning of parameters for a regression model to train the SAE for a regression problem. The method comprises generating a regression model for the SAE for solving the regression problem, wherein regression model is formulated as a non-convex joint optimization function for an asymmetric SAE. The method further comprises reformulating the non-convex joint optimization function as an Augmented Lagrangian formulation in terms of a plurality of proxy variables and a plurality of hyper parameters. The method comprises splitting the Augmented Lagrangian formulation into sub-problems using Alternating Direction Method of Multipliers and jointly learning parameters for the regression model to train the SAE for the regression problem. The learned weights enable estimating the unknown target values.

公开(公告)号：US20220327336A1

公开(公告)日：2022-10-13

申请号：US17368584

申请日：2021-07-06

Applicant: Tata Consultancy Services Limited

Inventor： Tanushyam Chattopadhyay ,  ABHISEK DAS ,  PRATEEP MISRA ,  SHUBHRANGSHU GHOSH ,  SUVRA DUTTA

IPC: G06K9/62

Abstract: Industries deploy a plethora of sensors that are attached to a system or human being, respectively. Under multi-sensor environment scenarios, there is a need to detect which sensors are behaving similarly within a time span. Sensor values often vary in range of values yet depict similar time series characteristic and sometimes have a phase difference in operation, thus making it impossible to detect such sensor similarity in a large system where the number of input parameters/sensor observations. Systems and methods of the present disclosure determine similar behavioral pattern between time series data obtained from multiple sensors and cluster the sensors. The system implements a pattern recognition-based approach to find the similarity and then applies a Dynamic Programming-based approach to detect similarity in at least two time series data and cluster the sensors and corresponding time series data into specific cluster(s).

公开(公告)号：US11449522B2

公开(公告)日：2022-09-20

申请号：US17359818

申请日：2021-06-28

Applicant: Tata Consultancy Services Limited

Inventor： Tanushyam Chattopadhyay ,  Arindam Halder ,  Sangram Dasharath Gaikwad ,  Tania Ghosh ,  Abhisek Das ,  Shubhrangshu Ghosh ,  Suvra Dutta ,  Prateep Misra

IPC: G06F17/00 ,  G06F16/25 ,  G06F16/2455

Abstract: Sensor data (or IoT) analytics plays a critical role in taking business decisions for various entities (e.g., organizations, project owners, and the like). However, scaling of such analytical solutions beyond certain point requires adopting to various computing environments which seems to be challenging with the constrained resources available. Embodiments of the present disclosure provide system and method for analysing and executing sensor observational data in computing environments, wherein extract, transform, load (ETL) workflow pipeline created by users in the cloud, can be seamlessly deployed to job execution service available in cloud/edge without any changes in the code/config by end user. The configuration changes are internally handled by the system based on the selected computing environment and queries are executed either in distributed or non-distributed environments to output data frames. The data frames are further pre-processed in a desired computing environment and thereafter visualized accordingly.

公开(公告)号：US09830736B2

公开(公告)日：2017-11-28

申请号：US14767161

申请日：2014-01-22

Applicant: Tata Consultancy Services Limited

Inventor： Aniruddha Sinha ,  Tanushyam Chattopadhyay ,  Sangheeta Roy ,  Apurbaa Mallik

IPC: G06T15/08 ,  G06T7/20 ,  G06T7/50 ,  G06T7/11 ,  G06T7/187

CPC classification number: G06T15/08 ,  G06T7/11 ,  G06T7/187 ,  G06T7/20 ,  G06T7/50 ,  G06T2207/10016 ,  G06T2207/10024 ,  G06T2207/10028 ,  G06T2207/30196 ,  G06T2207/30232

Abstract: Disclosed is a method for segmenting a plurality of objects from a two-dimensional (2D) video captured through a depth camera and an RGB/G camera. The method comprises detecting camera motion in each 2D frame of the plurality of 2D frames from the 2D video and generate a first set of 2D frames without any camera motion. The method further comprises generating a plurality of cloud points for the first set of 2D frames corresponding to each pixel associated a 2D frames in the first set of 2D frames. The method further comprises generating a 3D grid comprising a plurality of voxels. The method further comprises determining valid voxels and an invalid voxels in the 3D grid. Further, a 3D connected component labeling technique is applied on to the set of valid voxels to segment the plurality of objects in the 2D video.

公开(公告)号：US09117132B2

公开(公告)日：2015-08-25

申请号：US14081871

申请日：2013-11-15

Applicant: TATA CONSULTANCY SERVICES LIMITED

Inventor： Tanushyam Chattopadhyay ,  Bidyut B. Chaudhuri

IPC: G06K9/18 ,  G06K9/32 ,  G05B13/02

CPC classification number: G06K9/18 ,  G06K9/3266 ,  G06K9/6282

Abstract: The present disclosure relates to designing of a hierarchy of feature vectors. In one embodiment, a method for facilitating design of a hierarchy of feature vectors while recognizing one or more characters in a video is disclosed. The method comprises collecting one or more features from each of the segments in a video frame extracted from a video; preparing multi-dimensional feature vectors to classify the one or more characters; calculating a minimum distance between the multi-dimensional features vectors of a test character and the multi-dimensional feature vectors of a pre-stored character template; selecting, with respect to a decreasing order of the minimum distance, the multi-dimensional feature vectors to design a hierarchy of the multi-dimensional feature vectors; and classifying the characters based on the hierarchy of the multi-dimensional feature vectors.

Abstract translation: 本公开涉及特征向量的层次结构的设计。 在一个实施例中，公开了一种便于在识别视频中的一个或多个字符的同时设计特征向量的层次的方法。 该方法包括从从视频提取的视频帧中的每个段收集一个或多个特征; 准备多维特征向量来分类一个或多个字符; 计算测试人物的多维特征向量与预先存储的角色模板的多维特征向量之间的最小距离; 针对所述最小距离的递减次序选择所述多维特征向量来设计所述多维特征向量的层级; 并且基于多维特征向量的层次来对角色进行分类。

公开(公告)号：US20150186724A1

公开(公告)日：2015-07-02

申请号：US14576627

申请日：2014-12-19

Applicant: Tata Consultancy Services Limited

Inventor： Ramu Reddy Vempada ,  Tanushyam Chattopadhyay

IPC: G06K9/00 ,  G06K9/52

CPC classification number: G06K9/00624 ,  A61B5/1123 ,  A61B5/1128 ,  A61B5/7267 ,  G06F3/017 ,  G06F19/00 ,  G06K9/00342 ,  G06K9/00348 ,  G06K9/44 ,  G06K9/52 ,  G06K9/6269

Abstract: A System and method for identifying one or more human activities in a human-computer interacting environment. Skeleton points associated with a human are received. A data variation factor for the skeleton points is calculated, and a set of skeleton points is selected based on the data variation factor. One or more features are defined from the set of skeleton points by identifying a variance in coordinates of the set of skeleton points by using one or more statistical parameters. The one or more features are used to identify the one or more human activities.

Abstract translation: 一种用于识别人机交互环境中的一个或多个人类活动的系统和方法。 收到与人相关联的骨骼点。 计算骨架点的数据变化因子，并根据数据变异因子选择一组骨架点。 通过使用一个或多个统计参数来识别该组骨架点的坐标方差，从该组骨骼点定义一个或多个特征。 一个或多个特征用于识别一个或多个人类活动。

公开(公告)号：US20150031965A1

公开(公告)日：2015-01-29

申请号：US14444745

申请日：2014-07-28

Applicant: TATA CONSULTANCY SERVICES LIMITED

Inventor： Aishwarya Visvanathan ,  Arpan Pal ,  Anirban Dutta Choudhury ,  Tanushyam Chattopadhyay ,  Anurag Kumar ,  Rohan Banerjee ,  Aniruddha Sinha

IPC: A61B5/00 ,  A61B5/1455 ,  A61B5/0402 ,  A61B5/0205

CPC classification number: A61B5/0059 ,  A61B5/0205 ,  A61B5/021 ,  A61B5/02416 ,  A61B5/02438 ,  A61B5/04028 ,  A61B5/08 ,  A61B5/14551 ,  A61B5/6898 ,  A61B5/7267 ,  A61B2505/07 ,  G06F19/00

Abstract: A method for monitoring physiological parameters associated with a subject using a hand held device is described herein. In an implementation, the method includes obtaining a plurality of sample photoplethysmographic (PPG) features associated with a sample subject, from a video of a body part of the sample subject. From among the plurality of sample PPG features, at least one relevant sample PPG feature associated with the physiological parameter, is selected based on a ground truth value of the physiological parameter for the subject. Further, based on the at least one relevant sample PPG feature and the ground truth value of the physiological parameter, a mathematical model indicative of a correlation between the relevant sample PPG feature and the physiological parameter, is determined. The mathematical model can be deployed for monitoring the physiological parameter in real time.

Abstract translation: 本文描述了使用手持式装置监测与受试者相关的生理参数的方法。 在一个实现中，该方法包括从样本对象的身体部分的视频获得与样本对象相关联的多个样本光体积描记图（PPG）特征。 从多个样本PPG特征中，基于对象的生理参数的基本真值，选择与生理参数相关联的至少一个相关样本PPG特征。 此外，基于至少一个相关样本PPG特征和生理参数的基本真值，确定指示相关样本PPG特征和生理参数之间的相关性的数学模型。 可以部署数学模型，实时监测生理参数。