Abstract: Textual overlays/labels add contextual information in Augmented Reality (AR) applications. The spatial placement of labels is a challenging task particularly for real time videos. Embodiments of the present disclosure provide systems and methods for optimal placement of contextual information for Augmented Reality (AR) applications to overcome the limitations of occlusion with object/scene of interest through optimally placing labels aiding better interpretation of scene. This is achieved by combining saliency maps computed for each frame of an input video with Euclidean distance between current and previous overall positions for each frame based on an initial overlay position of the label to calculate an updated overlay position for label placement in the video. The placement of overlays is formulated as an objective function that minimizes visual saliency around the object of interest and minimizes the temporal jitter facilitating coherence in real-time AR applications.

Abstract: System and method of the present disclosure provide a linguistic approach to image processing. Prior art focused on extracting well-defined single objects occupying large portion of an image area. However, there was no focus on higher level semantics or distribution of object categories within the image. In contrast to imagery by handheld devices, remotely sensed data contains numerous objects because of relative large coverage and distribution over objects is critical to analyzing such large coverage. Accordingly, in the present disclosure, a generative statistical model is defined wherein an aerial image is modelled as a collection of the one or more themes and each of the one or more themes is modelled as a collection of object categories. The model automatically adapts to a scale of the aerial image and appropriately identifies the themes which may be used for applications including monitoring land use, infrastructure management and the like.

Abstract: Robotic applications are important in both indoor and outdoor environments. Establishing reliable end-to-end communication among robots in such environments are inevitable. Many real-time challenges in robotic communications are mainly due to the dynamic movement of robots, battery constraints, absence of Global Position System (GPS), etc. Systems and methods of the present disclosure provide assisted link prediction (ALP) protocol for communication between robots that resolves real-time challenges link ambiguity, prediction accuracy, improving Packet Reception Ratio (PRR) and reducing energy consumption in-terms of lesser retransmissions by computing link matrix between robots and determining status of a Collaborative Robotic based Link Prediction (CRLP) link prediction based on a comparison of link matrix value with a predefined covariance link matrix threshold. Based on determined status, robots either transmit or receive packet, and the predefined covariance link matrix threshold is dynamically updated.

Abstract: Systems and methods of the present disclosure facilitate rigid point cloud registration with characteristics including shape constraint, translation proportional to distance and spatial point-set distribution model for handling scale. The method of the present disclosure enables registration of a rigid template point cloud to a given reference point cloud. Shape-constrained gravitation, as induced by the reference point cloud, controls movement of the template point cloud such that at each iteration, the template point cloud better aligns with the reference point cloud in terms of shape. This enables alignment in difficult conditions introduced by change such as presence of outliers and/or missing parts, translation, rotation and scaling. Also, systems and methods of the present disclosure provide an automated method as against conventional methods that depended on manually adjusted parameters.

Abstract: The present subject matter discloses system and method for executing prescriptive analytics. Simulation is performed from an input data (xinput) and simulation parameters (?) to generate simulating data (D). Further, forecast data may be predicted by processing the simulating data (D) using predictive model (M). Further, prescriptive value (x?) may be determined based on the forecast data by using optimization model. The prescriptive value (x?) may be determined such that an objective function associated with the optimization model is optimized, whereby the optimization of the objective function indicates business objective being achieved. Further, the steps of simulating, predicting and determining may be iteratively performed until the objective function is not further optimized, satisfying predefined condition.

Abstract: Systems and methods for a dense surface reconstruction of an object using graph signal processing is provided. None of the traditional systems and methods provide for a dense or three-dimensional surface reconstruction of objects by resolving ? ambiguity. The embodiments of the proposed disclosure provide for resolving ? ambiguity by identifying, from one or more sparse three-dimensional shapes extracted, a first set of azimuth values corresponding to a first region of the object; constructing, using a phase angle, a graph capturing a relational structure between the first set of azimuth values and a second set of azimuth values to be estimated; obtaining, a Graph Fourier Transform (GFT) matrix corresponding to the constructed graph; and estimating, from the GFT matrix and the first set of azimuth values, the second set of azimuth values corresponding to a second region of the object by the graph signal processing technique.

Abstract: Electrocardiography (ECG) signals contain important markers for Coronary Heart Disease (CHD). State of the art systems and methods rely on clinically available multi-lead ECG for CHD classification which is not cost effective. Moreover the state of the art methods are applied on digital ECG time series data only. Also, discriminative HRV markers are not often present in short ECG recordings necessitating long hours of ECG data to analyze. In accordance with the present disclosure, systems and methods described hereinafter extract ECG time series from ECG images obtained from commercially available low-cost single lead ECG devices through a combination of image and signal processing steps including Histogram analysis, Morphological operation-thinning, Extraction of lines, Extraction of Reference Pulse, Extraction of ECG and interpolating missing data.

Abstract: This disclosure relates generally to speech signal processing, and more particularly to method and system for improving recognition of disordered speech. In one embodiment, a method and a system for identifying extent of deviation in speech utterances of a user from a normal level, caused due to such impairments are provided. The system further makes appropriate modifications to generate utterances pertaining to healthy speech. This data may be fed as input to the speech recognition systems, as those systems can interpret the corrected data.

Abstract: The use of gestures are increasing frequently. Normally these gestures are disconnected with each other. Therefore, various methods have been used for creating the gestural language. The existing methods for creating gestural language is difficult to learn and lacks design aesthetics. A method and system for creating aesthetic design language using a plurality of gestures is provided. The system takes in to account of aesthetics of the generated form of gestures and the user's constraints of movement—degrees of freedom. The system is using a socio-techno system which aids the machine assisted creation of aesthetic language for gestural interactions. A grammar has also been defined for creating the gestural language based on the domain. In the final stage of the system, the grammar and the form symbols are chosen/selected/published to present the interaction language to the user.

Abstract: A method and system for interpreting a dataset is described herein. The method include computing a rule set pertaining to the dataset, followed by generating a rule cover pertinent to a subset of the rule set. Further, a plurality of distances between the plurality of rule pairs in the rule cover is calculated and a distance matrix based on the calculated plurality of distances is generated. Consequently, the overlapping rules within the rule cover are clustered using the distance matrix and a representative rule from each cluster is selected. Further, at least one exception for each representative rule is determined and the dataset is interpreted using the representative rules and the at least one exception. Thereby, the method provides succinct results in terms of rules and exceptions along with multiple interpretations of the same set of transactions from the dataset, thereby providing a holistic view about the dataset.

Abstract: The method(s) and system(s) for implementing extensibility of computational design and modelling of subject area on a computational platform in respect of a new subject in a subject area through a modelling schema includes populating the new subject in the model repository as data elements corresponding to the domain entity model of the domain entity meta model. The method includes generating a subject integration layer and a subject information interaction layer from the populated subject data elements and generating GUI screens for user interactions from the populated subject data elements. The method, further, includes integrating user determined external simulation tools with the computational platform by mapping the user determined external simulation tool parameters to the subject data elements. Subsequently, the method includes generating simulation tool adapters from said mapping to achieve said integration.

Abstract: Conventional systems for monitoring pipe networks are generally not scalable, impractical in the field with uncontrolled environments or rely of static features of pipes that are vary depending on the pipes under consideration. The ideal sensor-ed monitoring systems are not economically viable. Systems and methods of the present disclosure provide an improved data-driven model to rank pipes in the order of burst probabilities, by including dynamic feature values of pipes such as pressure and flow that depends on network structure and operations. The present disclosure enables estimating approximate values for the dynamic features since they are hard to estimate accurately in the absence of a calibrated hydraulic model. The present disclosure also validates the estimated approximate dynamic feature values for the purpose of estimating bursts likelihood vis-a-vis accurate values of the dynamic metrics.

Abstract: The present disclosure provides a method and system that estimates size, effort and FTE of software Managed Services Production Support (MS-PS) engagements. It provides a method and system to categorize all applications in various bundles based on multiple parameters. Further the invention provides a method and system to estimates size of each bundle at an application level based on a set of variables. Further, the invention provides a method and system for utilizing the estimated MS-PS engagement size and organizational baseline productivity information for estimating the MS-PS engagement base effort which can then be adjusted based on multiple factors to arrive at the final effort. It estimates full time equivalent (FTE) of the MS-PS engagement using the final estimated effort of the applications and additional FTE impacting parameters. The invention furthermore provides a method and system to optimize the estimated FTE for a bundle and view the overall unutilized effort.

Abstract: There are many administrative processes which require a user to enter handwritten data on ordinary paper forms. This data is then further processed and converted in the digitized form. In the existing methods, the turnaround time for whole process is high, lacks accuracy of the digitized data, and cost is also on the higher side. A system and method for real time digitization of hand written input data has been provided. The system comprises an input device that utilizes a pen and paper input form which is filled by a user in his hand writing. The completed form data is then transferred to a form inspector application that runs on the aggregation device. It allows for applications to be verified for completeness and send the same for real-time digitization using a form processor application. A recognition engine is then used for the digitization of the hand written input data.

Abstract: This disclosure relates generally to a system and method to identify at least one conflict and for controlling both static and dynamic variables in one or more operations of at least one subsystem of a plurality of building automation sub-systems. It includes a supervisory control layer that orchestrates multiple underlying sub-systems like heating, ventilation, and air-conditioning (HVAC) sub-systems and at least one access control sub-system. A test case generation framework is used to verify static and dynamic variables of operations of the sub-systems. It identifies conflicts in the static and dynamic variables. Therefore, the system provides controls to the sub-systems using the identified and adjusted conflict of static and dynamic variables on operations.

Abstract: Metallic alloy development has been traditionally based on experimental or theoretical equilibrium phase diagrams and the like. The synthesis, processing and mechanical testing of small and large real samples are a challenging task requiring huge amount of effort in terms of time, money, resource, tedious testing and processing equipment and man-hour for which conventional Calphad calculations etc. alone do not help much in their local structure and related property prediction. Embodiments of the present disclosure provide simulation systems and methods for structure evolution and property prediction Molecular Dynamics (MD) combined with accelerated Monte Carlo techniques, wherein information on atomic elements and composition specific to alloy material is obtained to generate a MD potential file that is further used to generate a 3D structure file by executing a structure equilibration technique.

Abstract: Disclosed is method and system for modeling and executing service operation associated with technical service. Method comprises modeling of knowledge required for execution of service operation by representing factual knowledge and actionable knowledge in executable form. Modeling comprises representing standard operators and service operation. Service operation comprises parameters and rules presented in form of list of predicate-action pairs. Predicate-action pair comprises predicate and action. Predicate defines condition to be verified to comply with rule, and action specifies standard operator to be executed based on verification of condition. Method further comprises execution of service operation.

Abstract: Automatic steering control is essential part for autonomous vehicle which controls the steering in various scenarios to achieve safe and comfortable driving. The present subject matter discloses a system and method for steering control during autonomous vehicle driving using neural networks. In an embodiment, a lane side offset, a radius of curvature and a speed of a vehicle are received. Further, an ideal steering angle required to keep the vehicle at a center of a lane is determined using the radius of curvature. Furthermore, an offset error is determined based on the lane side offset using a reference offset. In addition, a corrective steering angle is determined using the radius of curvature, speed of the vehicle and offset error. Also, a steering angle required to keep the vehicle at a center of a lane is computed using the ideal steering angle and the corrective steering angle.

Abstract: A method and system is provided for vehicle speed profile generation. The method is performed by receiving data pertaining to driver characteristics and characteristics of trips taken by said driver, creating driver profile by generating skill and aggression parameters for said driver, constructing trip parameters pertaining to said trips taken by the driver by processing the skill and aggression parameters, constructing acceleration dataset for said trips, constructing speed values from the acceleration dataset and processing the speed values for anomalies.

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.