Tata Consultancy Services Limited

Ehtesham Hassan

Ramya Sugnana Murthy Hebbalaguppe

Puneet Kumar Agarwal

Gaurav Gupta

Gautam Shroff

Lovekesh Vig

Monika Sharma

Swagat Kumar

Hiranmay Ghosh

Ashwin Srinivasan

Shilpa Yadukumar Rao

Jitender Kumar Maurya

Ramakrishna Perla

RamaKrishna Perla

Guatam Shroff

Preeti Johri

Mohit Yadav

Gaurav

Ankit Verma

Olyvia Kundu

Archie Gupta

Anurag Saran

Surya Yadav

A method and system is provided for planogram compliance check based on visual analysis. The present method and system comprises acquiring a product shelf image, identifying a region of interest (ROI) from the at least one product shelf image, extracting a perspective distortion rectification of the identified ROI to generate a rectified shelf image, applying Hausdroff distance based image map for occupancy estimation in shelf images extracting one or more rows from the rectified shelf image wherein the rectified shelf image comprises a plurality of horizontal row partitions, and deriving a product count and placement information for each of the extracted one or more rows based on the extracted rows and the occupancy estimation.

Method and system for planogram compliance check based on visual analysis

This disclosure relates generally to ROI marking, and more particularly to system and method for marking ROI in a media stream using touchless hand gesture interface such as headmount devices. In one embodiment, the method includes recognizing a pointing object representative of a gesture in frames of the media stream while capturing the media stream. The media stream comprises a scene captured from a first person view (FPV) of a user. Locus of the pointing object is detected in subsequent frames subsequent of the media stream to select a ROI in the media stream. The locus of the pointing object configures a bounding box around the ROI. The ROI is tracked in frames of the media stream occurring subsequent to the subsequent frames in the media stream. The bounding box is updated around the ROI based on the tracking, wherein the updated bounding box encloses the ROI.

Telepresence framework for region of interest marking using headmount devices

Systems and methods for detecting and tracking a marker in real time is disclosed. Shape based segmentation of at least one object detected in a first frame from a sequence of frames is performed to define a region of interest (ROI) surrounding an object of interest corresponding to the marker. A marker detection model is dynamically trained based on sampling points from a plurality of pixels in and around the ROI. The marker is then tracked in real-time based on projected ROI in subsequent frames and the trained marker detection model. To optimize computation time required in classifying the pixels as marker pixels or non-marker pixels, the ROI is reduced to half its size, classification is performed on the reduced ROI and to improve accuracy, blob detection and classifying pixels along the boundary of the reduced ROI is performed by processing the ROI in original resolution.

Systems and methods for detecting and tracking a marker

Systems and methods for detecting grasping poses for handling target objects is disclosed. The system solves problem of grasp pose detection and finding suitable graspable affordance for picking objects from a confined and cluttered space, such as the bins of a rack in a retail warehouse by creating multiple surface segments within bounding box obtained from a neural network based object recognition module. Surface patches are created using a region growing technique in depth space based on surface normals directions. A Gaussian Mixture Model based on color and depth curvature is used to segment surfaces belonging to target object from background, thereby overcoming inaccuracy of object recognition module trained on a smaller dataset resulting in larger bounding boxes for target objects. Target object shape is identified by using empirical rules on surface attributes thereby detecting graspable affordances and poses thus avoiding collision with neighboring objects and grasping objects more successfully.

Systems and methods for detecting grasp poses for handling target objects

This disclosure relates generally to character detection and recognition, and more particularly to a method and system for container code recognition via Spatial Transformer Networks and Connected Component. The method comprises capturing an image of a container using an image capture device which is pre-processed using an image preprocessing module. The method further comprises extracting and filtering region proposals from the pre-processed image using a region extraction module to generate regrouped region proposals. The next step comprises classifying the regrouped region proposals into characters by implementing trained Spatial Transformation Network to generate a valid group of region proposal with more than one chunk of container identification code using a classification module, and lastly a sequence for the valid group of region proposal is generated and the generated sequence is mapped to a predefined standard container identification code to determine a container identification code, wherein the predefined standard identification code comprises chunks of characters in a predefined pattern.

Method and system for container code recognition

This disclosure relates generally to telecom inventory management, and more particularly to telecom inventory management via object recognition and localization using street-view images. In one embodiment, the method includes obtaining street-view images of a geographical area having telecom assets. The telecom assets are associated with corresponding GPS location coordinates. An object recognition model is applied to the street-view images to detect the telecom assets therein. Detecting the telecom assets includes associating the telecom assets with corresponding asset labels. A real-world location of the telecom assets is estimated in the geographical area by applying triangulation method on a set of multi-view images selected from the street-view images. The set of multi-view images are captured from a plurality of consecutive locations in vicinity of the telecom asset in the geographical area. The GPS location coordinates of the telecom assets are validated based at least on the estimated real-world location.

System and method for telecom inventory management

The present subject matter discloses a system and a method for detecting an event from time-series data sequences. The system receives time-series data sequences generated by sensors, wherein the time-series data sequences comprise sample points. The system pairs the sample points with one another for determining pairs of the sample points. The system computes Euclidean distances and angles between the sample points for determining distance matrix and angle matrix corresponding to the sample points. Further, the system determines global distribution of the plurality of pairs of sample points, wherein the global distribution of the plurality of pairs of sample points represent 2D shape histogram for the time-series data sequence. Further, the system concatenates the 2D shape histogram for each time-series data sequence to generate a concatenated shape histogram. Finally the system matches the concatenated shape histogram to pre-stored shape histograms for determining the event.

Detecting an event from time-series data sequences

Methods and systems for searching logical patterns in voluminous multi sensor data from the industrial internet is provided. The method retrieves instances of patterns in time-series data where patterns are specified logically, using a sequence of symbols. The logical symbols used are a subset of the qualitative abstractions specifically, the concepts of steady, increasing, decreasing. Patterns can include symbol-sequences for multiple sensors, approximate duration as well as slope values for each symbol. To facilitate efficient querying, each sensor time-series is pre-processed into a sequence of logical symbols. Each position in the resulting compressed sequence is registered across a TRIE-based index structure corresponding to the multiple logical patterns it may belong to. Logical multi-sensor patterns are efficiently retrieved and ranked using such a structure. This method of indexing and searching provides an efficient mechanism for exploratory analysis of voluminous multi-sensor data.

Methods and systems for searching logical patterns

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Gurgaon, India

Ehtesham Hassan