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公开(公告)号：US09208376B2
公开(公告)日：2015-12-08
申请号：US14280353
申请日：2014-05-16
Applicant: TATA CONSULTANCY SERVICES LIMITED
Inventor： Kingshuk Chakravarty , Aniruddha Sinha , Diptesh Das , Rohan Banerjee , Amit Konar , Sudeepto Dutta
CPC classification number: G06K9/00348 , G06K9/44 , G06K9/627
Abstract: Method(s) and system(s) for identification of an unknown person are disclosed. The method includes receiving skeleton data comprises data of multiple skeleton joints of the unknown person from skeleton recording devices. The method further includes extracting G gait feature vectors from the skeleton data. Further, the method includes classifying each gait feature vector into one of N classes based on a training dataset for N known persons and computing a classification score for each class. The method also includes clustering the training dataset into M clusters based on M predefined characteristic attributes of the known persons, tagging each gait feature vector with one of the M clusters based on a distance between a respective gait feature vector and cluster centers of M clusters, and determining a clustering score for each M cluster. The method further includes identifying the unknown person based on clustering scores and classification scores.
Abstract translation: 公开了用于识别未知人的方法和系统。 该方法包括从骨架记录装置接收包括未知人的多个骨骼关节的数据的骨架数据。 该方法还包括从骨架数据中提取G步态特征向量。 此外，该方法包括基于N个已知人员的训练数据集将每个步态特征向量分类为N类中的一个，并计算每个类的分类分数。 该方法还包括基于已知人员的M个预定义特征属性将训练数据集聚类成M个群集，基于各个步态特征向量与M个群集的簇中心之间的距离来标记每个步态特征向量与M个群集中的一个， 以及确定每个M簇的聚类分数。 该方法还包括基于聚类分数和分类分数识别未知人。
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公开(公告)号：US10068333B2
公开(公告)日：2018-09-04
申请号：US15466676
申请日：2017-03-22
Applicant: Tata Consultancy Services Limited
Inventor： Sanjana Sinha , Brojeshwar Bhowmick , Kingshuk Chakravarty , Aniruddha Sinha , Abhijit Das
Abstract: Systems and methods for identifying body joint location includes obtaining skeletal data, depth data and red, green, and blue (RGB) data pertaining to a user, obtaining, using input data, an estimate of body joint locations (BJLs) and body segment lengths (BSLs), iteratively identifying, based on the depth data and RGB data, probable correct BJLs in a bounded neighborhood around BJLs that are previously obtained, comparing a body segment length associated with the probable correct BJLs and a reference length, identifying candidate BJLs based on comparison, determining a physical orientation of each body segment by segmenting three dimensional (3D) coordinates of each body segment based on the depth data and performing an analysis on each segmented 3D coordinate. A corrected BJL is identified based on a minimal deviation in direction from the physical orientation of a corresponding body segment along with a feature descriptor of the RGB data and depth data.
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公开(公告)号：US20150193686A1
公开(公告)日：2015-07-09
申请号：US14588595
申请日：2015-01-02
Applicant: Tata Consultancy Services Limited
Inventor： Kingshuk Chakravarty , Ramu Reddy Vempada , Tanushyam Chattopadhyay , Aniruddha Sinha , Arpan Pal
CPC classification number: G06N5/04 , G01J5/00 , G06F21/32 , G06K9/00369 , G06K2209/055 , G06N99/005
Abstract: A system and method for identifying an unknown person based on a static posture of the unknown person is described. The method includes receiving data of N skeleton joints of the unknown person from a skeleton recording device. The method further includes identifying the static posture of the unknown person. The method includes dividing a skeleton structure of the unknown person in a plurality of body parts based on joint types of the skeleton structure. In addition, the method includes extracting feature vectors for each of the joint type from each of the plurality of body parts. The method further includes identifying the unknown person based on comparison of the feature vectors for the unknown person with one of a constrained feature dataset and an unconstrained feature dataset for a plurality of known persons.
Abstract translation: 描述了基于未知人的静态姿势来识别未知人的系统和方法。 该方法包括从骨架记录装置接收未知人的N个骨架关节的数据。 该方法还包括识别未知人的静态姿势。 该方法包括基于骨骼结构的关节类型将未知人的骨架结构划分为多个身体部位。 此外，该方法包括从多个身体部分中的每一个提取每个关节类型的特征向量。 该方法还包括基于未知人的特征向量与多个已知人的约束特征数据集和无约束特征数据集之一的比较来识别未知人。
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4.发明申请MULTIMODAL SYSTEM AND METHOD FACILITATING GESTURE CREATION THROUGH SCALAR AND VECTOR DATA 有权多模式系统和方法通过标量和矢量数据促进创造力公开(公告)号：US20150049016A1
公开(公告)日：2015-02-19
申请号：US14387007
申请日：2013-03-08
Applicant: Tata Consultancy Services Limited
Inventor： Aniruddha Sinha , Kingshuk Chakravarty , Rohit Kumar Gupta , Arpan Pal , Anupam Basu
IPC: G06F3/01
CPC classification number: G06F3/017 , A63F13/213 , A63F13/215 , G06F3/011 , G06K9/00335 , G06K9/629 , G06K9/6293
Abstract: A device and a method facilitating generation of one or more intuitive gesture sets for the interpretation of a specific purpose are disclosed. Data is captured in a scalar and a vector form which is further fused and stored. The intuitive gesture sets generated after the fusion are further used by one or more components/devices/modules for one or more specific purpose. Also incorporated is a system for playing a game. The system receives one or more actions in a scalar and a vector from one or more user in order to map the action with at least one pre stored gesture to identify a user in control amongst a plurality of users and interpret the action of user for playing the game. In accordance with the interpretation, an act is generated by the one or more component of the system for playing the game.
Abstract translation: 公开了一种便于产生用于解释特定目的的一个或多个直观手势集的装置和方法。 以标量和向量形式捕获数据，进一步融合和存储。 一个或多个组件/设备/模块进一步使用融合之后生成的直觉手势集合用于一个或多个特定目的。 还包括玩游戏的系统。 系统从一个或多个用户接收标量和向量中的一个或多个动作，以便通过至少一个预先存储的手势来映射动作，以便在多个用户之间的控制中识别用户，并解释用户播放的动作 游戏。 根据解释，系统的一个或多个部件产生一个动作，用于玩游戏。
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公开(公告)号：US11596328B2
公开(公告)日：2023-03-07
申请号：US15914286
申请日：2018-03-07
Applicant: Tata Consultancy Services Limited
Inventor： Oishee Mazumder , Kingshuk Chakravarty , Debatri Chatterjee , Aniruddha Sinha , Abhijit Das
Abstract: This disclosure relates generally to health monitoring and assessment systems, and more particularly to perform postural stability assessment of a user and quantify the assessed postural stability. In an embodiment, the system, by monitoring specific actions (which are part of certain tests done for the postural stability assessment) being performed by a user, collects inputs which are then processed to determine SLS duration, the body joint vibration, and the body sway area of the user, while performing the tests. By processing the SLS duration, the body joint vibration, and the body sway area together, a postural stability index score for the user is determined, and based on this score, postural stability assessment for the user is performed.
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Patent Agency Ranking
公开(公告)号：US11033205B2
公开(公告)日：2021-06-15
申请号：US15427762
申请日：2017-02-08
Applicant: Tata Consultancy Services Limited
Inventor： Kingshuk Chakravarty , Brojeshwar Bhowmick , Aniruddha Sinha , Abhijit Das
Abstract: A method and system is provided for finding and analyzing gait parameters and postural balance of a person using a Kinect system. The system is easy to use and can be installed at home as well as in clinic. The system includes a Kinect sensor, a software development kit (SDK) and a processor. The temporal skeleton information obtained from the Kinect sensor to evaluate gait parameters includes stride length, stride time, stance time and swing time. Eigenvector based curvature detection is used to analyze the gait pattern with different speeds. In another embodiment, Eigenvector based curvature detection is employed to detect static single limb stance (SLS) duration along with gait variables for evaluating body balance.
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公开(公告)号：US11000222B2
公开(公告)日：2021-05-11
申请号：US16523491
申请日：2019-07-26
Applicant: Tata Consultancy Services Limited
Inventor： Kingshuk Chakravarty , Aniruddha Sinha , Soumya Rajan Tripathy
Abstract: Skeletal recording devices (e.g., Microsoft Kinect®) has been gaining popularity in home-based rehabilitation solution due to its affordability and ease of use. It is used as a marker less human skeleton tracking device. However, apart from the fact that the skeleton data are contaminated with high frequency noise, the major drawback lies in the inability to retain the anthropometric properties, for example, the body segments' length, which varies with time during the tracking. Embodiments of the present disclosure provide systems that implement a particle filter based approach to track the human skeleton data in presence of high frequency noise and multi-objective genetic technique is further implemented to reduce the bone length variations. Further multiple segments in skeleton are filtered simultaneously and segments' lengths are preserved by considering their interconnection for obtained corrected set of body joint positions which ensures that the body segment length is maintained close to ground truth.
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公开(公告)号：US11468977B2
公开(公告)日：2022-10-11
申请号：US16587309
申请日：2019-09-30
Applicant: Tata Consultancy Services Limited
Inventor： Sangheeta Roy , Oishee Mazumder , Kingshuk Chakravarty , Debatri Chatterjee , Aniruddha Sinha
Abstract: Collision avoidance and postural stability adjustment may provide an effective dual task paradigm to interpret the effect of proprioceptive adaptation on balance control. However, conventionally tasks are physical tasks performed under supervision in specific set up environments. Implementations of the present disclosure provide methods and systems for interpreting neural interplay involving proprioceptive adaptation in a lower limb during a dual task paradigm. The disclosed method provides a better interpreting of the neuronal mechanisms underlying adaptation and learning of skilled motor movement and to determine the relationship of lower limb proprioceptive sense and postural stability by simulating integration of a Single Limb Stance (SLS) functionality test for postural stability and a single limb collision avoidance task, in an adaptive Virtual Reality (VR) environment provided to a subject.
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公开(公告)号：US10750972B2
公开(公告)日：2020-08-25
申请号：US15912341
申请日：2018-03-05
Applicant: Tata Consultancy Services Limited
Inventor： Anwesha Khasnobish , Kingshuk Chakravarty , Debatri Chatterjee , Aniruddha Sinha
IPC: A61B5/0496 , A61B5/00 , A61B3/113
Abstract: This disclosure relates generally to head movement noise removal from electrooculography (EOG) signals, and more particularly to systems and methods for wavelet based head movement artifact removal from electrooculography (EOG) signals. Embodiments of the present disclosure provide for head movement noise removal from the EOG signals by acquiring EOG signals of a user, filtering the acquired EOG signals to obtain a first set of filtered EOG signals, smoothening the first set of filtered EOG signals to obtain smoothened EOG signals, removing one or more redundant patterns and one or more direct current (DC) drifts from the smoothened EOG signals to obtain a second set of filtered EOG signals, and applying, a discrete wavelet transform on the second set of filtered EOG signals to filter a plurality of head movement noise from the second set of filtered EOG signals of the user.
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公开(公告)号：US10198694B2
公开(公告)日：2019-02-05
申请号：US14588595
申请日：2015-01-02
Applicant: Tata Consultancy Services Limited
Inventor： Kingshuk Chakravarty , Ramu Reddy Vempada , Tanushyam Chattopadhyay , Aniruddha Sinha , Arpan Pal
Abstract: A system and method for identifying an unknown person based on a static posture of the unknown person is described. The method includes receiving data of N skeleton joints of the unknown person from a skeleton recording device. The method further includes identifying the static posture of the unknown person. The method includes dividing a skeleton structure of the unknown person in a plurality of body parts based on joint types of the skeleton structure. In addition, the method includes extracting feature vectors for each of the joint type from each of the plurality of body parts. The method further includes identifying the unknown person based on comparison of the feature vectors for the unknown person with one of a constrained feature dataset and an unconstrained feature dataset for a plurality of known persons.
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