Tata Consultancy Services Limited

Jitender Kumar Maurya

Ramya Sugnana Murthy Hebbalaguppe

Ehtesham Hassan

Puneet Gupta

Ramya Hebbalaguppe

RamaKrishna Perla

Archie Gupta

A system and a method for verification of a source code are provided. There as many techniques available that can be used for verification of software codes, however, it is difficult to determine appropriate technique that can be utilized for verification of a given software code. In an embodiment, the system receives a source code encoded with one or more specifications to be verified. A static analysis of the source code is performed to identify program features of the source code. The program features may include, but are not limited to, multiple return paths, loops with an unstructured control flow, loops with arrays, short ranges and numerical loops. Based on the identification of the program features, verification techniques are applied to the source code for the verification. Each verification technique of the one or more verification techniques is applied for a predetermined period of time and in a predefined order.

Hand detection in first person view

Hand segmentation on wearable devices is a challenging computer vision problem with a complex background because of varying illumination conditions, computational capacity of device(s), different skin tone of users from varied race, and presence of skin color background. The present application provides systems and methods for performing, in real time, hand segmentation by pre-processing an input image to improve contrast and removing noise/artifacts. Multi Orientation Matched Filter (MOMF) is implemented and applied on the pre-processed image by rotating the MOMF at various orientations to form an edge image which comprises strong edges and weak edges. Weak edges are further removed using morphological operation. The edge image is then added to the input image (or pre-processed image) to separate different texture region in image. Largest skin-color blob is then extracted which is considered to be correct segmented hand.

Systems and methods for performing hand segmentation

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.

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Gurgaon, India

Jitender Kumar Maurya