Samsung Electronics Co., Ltd.

Anamika Sharma

Srenivas Varadarajan

Rahul Anand Sharma

Yohan J Roh

Yovan Sethi

Amar Kumar

The disclosure relates to methods and systems for non-linear mapping of motion-compensated DVS events to DVS images. In the non-linear mapping of motion-compensated DVS events to DVS images, the current pixel increments depend on the existing number of accumulated events at that location. Further, the initial events are given a larger weightage to preserve the tracked features which are used for bundle adjustment. Further, disclosure relates to methods and systems for representing polarity in single channel DVS Frame. As the polarity adds additional constraints on feature matching and therefore accurate optical flow is seen in the image. Moreover, disclosure relates to methods and systems for using event-density as a measure of input contrast after DVS event accumulation and this is used to determine the target range for contrast stretching.

Methods and systems for improving DVS features for computer vision applications

The present disclosure provides a method of analyzing an image captured from an imaging device. The method includes receiving one or more images captured from a camera over a predetermined time period. Feature extraction and tracking are executed with respect to the received images. One or more features are detected as untracked features during the feature extraction and tracking. A geometrical prediction is executed with respect to the untracked features to predict one or more features and thereby achieving the one or more untracked features as the one or more tracked features.

Methods and systems for restoration of lost image features for visual odometry applications

The embodiments herein provide a method of obtaining a weighted combination of dynamic vision sensor (DVS) measurements and contact image sensor (CIS) measurements for determining visual inference in an electronic device, the method includes receiving, by the electronic device, a DVS image and a CIS image from the image sensor; determining, by the electronic device, a plurality of parameters associated with the DVS image and feature velocities of a plurality of CIS features present in the CIS image; determining, by the electronic device, a determined DVS feature confidence based on the plurality of parameters associated with the DVS image; determining, by the electronic device, a determined CIS feature confidence based on the feature velocities of the plurality of features present in the CIS image; and calculating, by the electronic device, a weighted visual inference based on the determined DVS feature confidence and the determined CIS feature confidence.

Method of determining visual interference using a weighted combination of CIS and DVS measurement

A method for maintaining peak intensity frames is provided. The method includes receiving a plurality of frames, each of which has an associated frame intensity, from a camera sensor; selecting a preview frame and a previous preview frame from among the plurality of frames; performing a coarse phase detection based on a frame intensity of the previous preview frame and the preview frame to identify a trend of frame intensity; monitoring a plurality of transitional preview frames after the preview frame; detecting at least one transitional frame having a frame intensity less than a previous transitional frame; and selecting a next transitional frame as a succeeding preview frame after the preview frame based on a frame intensity of the at least one transitional frame.

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Karnataka, India

Anamika Sharma