Tata Consultancy Services Limited

Apurbaa Mallik

Brojeshwar Bhowmick

Aniruddha Sinha

Balamuralidhar Purushothaman

Tanushyam Chattopadhyay

Sanjana Sinha

Arindam Saha

Swapna Agarwal

Sangheeta Roy

Aishwarya Visvanathan

Sudeb Das

Method and System for estimating three dimensional measurements of a physical object by utilizing readings from inertial sensors is provided. The method involves capturing by a handheld unit, three dimensional aspects of the physical object. The raw recordings are received from the inertial sensors and are used to develop a raw rotation matrix. The raw rotation matrix is subjected to low pass filtering to obtain processed matrix constituted of filtered Euler angles wherein coordinates from the processed rotation matrix is used to estimate gravitational component along the three axis leading to determination of acceleration values and further calculation of measurement of each dimension of the physical object.

System and method for estimating three-dimensional measurements of physical objects

Methods and systems for change detection utilizing three dimensional (3D) point-cloud processing are provided. The method includes detecting changes in the surface based on a surface fitting approach with a locally weighted Moving Least Squares (MLS) approximation. The method includes acquiring and comparing surface geometry of a reference point-cloud defining a reference surface and a template point-cloud defining a template surface at local regions or local surfaces using the surface fitting approach. The method provides effective change detection for both, rigid as well as non-rigid changes, reducing false detections due to presence of noise and is independent of factors such as texture or illumination of an object or scene being tracked for changed detection.

Methods and systems for surface fitting based change detection in 3D point-cloud

Disclosed is a method and system for constructing a 3D structure. The system of the present disclosure comprises an image capturing unit for capturing images of an object. The system comprises of a gyroscope, a magnetometer, and an accelerometer for determining extrinsic camera parameters, wherein the extrinsic camera parameters comprise a rotation and a translation of the images. Further the system determines an internal calibration matrix once. The system uses the extrinsic camera parameters and the internal calibration matrix for determining a fundamental matrix. The system extracts features of the images for establishing point correspondences between the images. Further, the point correspondences are filtered using the fundamental matrix for generating filtered point correspondences. The filtered point correspondences are triangulated for determining 3D points representing the 3D structure. Further, the 3D structure may be optimized for eliminating reprojection errors associated with the 3D structure.

Constructing a 3D structure

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.

Segmenting objects in multimedia data

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Kolkata, India

Apurbaa Mallik