Samsung Electronics Co., Ltd.

Honeywell International Inc.

Lokesh Rayasandra Boregowda

Lalitha M Eswara

Alok Shankarlal Shukla

Sankaranarayanan Parameswaran

Prajit Sivasankaran Nair

Ankit Dhiman

Dong Soo Kim

Mohammed Ibrahim Mohideen

Bin Sai

Eun-sun Ahn

Pankaj Kumar Bajpai

Balvinder Singh

Vijendran Gopalan Venkoparao

Young Kwon Yoon

Adishesha Cs

Pranav Prakash Deshpande

Dinesh Ramegowda

Sarvesh

Venkat Ramana Peddigari

Saikat Kumar Das

Koushik Sinha

Sandeep Jana

Green Rosh K S

Mohamed M Ibrahim

Rajat Kumar Jain

Meruva Jayaprakash

Jayakrishna Alapati

Santle Camilus

Sujoy Saha

Sourabh Singh Yadav

Thirumaran Ekambaram

Anupama Rajagopal

Jong Hun Won

Hwa Yong Kang

Rituparna Sarkar

Ramasamy Kannan

Sagar Aggarwal

Vishakha S R

Pawan Prasad Bindigan Hariprasanna

Amita Badhwar

Rakesh Abothula

Aditi Singhal

Mahantesh Mallappa Ambi

Krishnamoorthy Dornadula

Ibrahim M Mohamed

Narasimba Gopalakrishna Pai

A method for removing an artifact in a high resolution image by an electronic device is provided. The method includes receiving the high resolution image comprising the artifact. Further, the method includes downscaling the high resolution image into a plurality of lower resolution images. Further, the method includes removing the artifact from the plurality of lower resolution images by applying at least one first machine learning model from a plurality of machine learning models on the plurality of lower resolution images. Further, the method includes generating a high resolution image free from the artifact by applying at least one second machine learning model from the plurality of machine learning models on an output from the at least one first machine learning model. The output from each of the machine learning model comprises a low resolution image free from the artifact.

Method and electronic device for removing artifact in high resolution image

A method for generating a three-dimensional (3D) model of an object includes receiving a two-dimensional (2D) view of at least one object as an input, measuring geometrical shape coordinates of the at least one object from the input, identifying texture parameters of the at least one object from the input, predicting geometrical shape coordinates and texture parameters of occluded portions of the at least one object in the 2D view by processing the measured geometrical shape coordinates of the at least one object, the identified texture parameters of the at least one object, and the occluded portions of the at least one object, and generating a 3D model of the at least one object by mapping the measured geometrical shape coordinates and the identified texture parameters to the predicted geometrical shape coordinates and the predicted texture parameters of the occluded portions of the at least one object.

Methods and systems for generating three dimensional (3D) models of objects

A method for animating a graphical object by an electronic device is provided. The method includes receiving, by the electronic device, the graphical object having at least one predefined portion to animate. The method includes receiving, by the electronic device, an audio to obtain spectral frequencies of the audio. The method includes determining, by the electronic device, at least one of an intensity of the spectral frequencies and at least one range of the spectral frequencies. The method includes generating, by the electronic device, at least one motion on the at least one predefined portion of the graphical object based on the at least one of the intensity of the spectral frequencies and the at least one range of the spectral frequencies.

Method and electronic device for automatically animating graphical object

An electronic device and a method for generating an augmented reality (AR) content in an electronic device are provided. The method includes determining a posture and an action of each object of the plurality of the objects in the scene displayed on a field of view of the electronic device, classifying the posture and the action of each object of the plurality of the objects in the scene, identifying an intent and an interaction of each object from the plurality of objects in the scene based on at least one of the classified posture and the classified action, and generating the AR content for the at least one object in the scene of at least one of the identified intent and the identified interaction of the at least one object.

Method and electronic device for generating AR content based on intent and interaction of multiple-objects

An electronic device is disclosed. The electronic device may comprise: an image sensor for acquiring raw image data corresponding to light of infrared band and visible light band, with respect to an external object; and a processor, wherein the processor is configured to: receive a request for acquiring the raw image data corresponding to the external object; on the basis of the request configured to be performed using a first function of the image sensor, generate an RGB image related to the external object by using first raw image data corresponding to the light of visible light band, obtained through the image sensor, and on the basis of the request configured to be performed using a second function of the image sensor, perform biometric authentication related to the external object by using second raw image data corresponding to the light of infrared band, obtained through the image sensor. In addition, various embodiments recognized through the specification are possible.

Electronic device for providing function by using RGB image and IR image acquired through one image sensor

A device and a method for capturing media by using a device including a plurality of flaps are provided. At least two flaps among the plurality of flaps each include at least one camera. The method includes analyzing preview images of the cameras based on a first media capture mode, adjusting a bend angle between the at least two flaps based on the analysis of the preview images to determine at least one baseline distance, and obtaining at least one media in the first capture mode at the at least one baseline distance.

Electronic device for capturing media using a bendable display and method thereof

A method for generating a high-dynamic-range (HDR) image using an imaging device is provided. The method includes capturing a long-exposure (LE) image, a short-exposure (SE) image, and an auto-exposure (AE) image of a scene, estimating motion information in the SE image and the LE image based on a reference image which is determined based on an image statistics parameter, aligning the SE image and the LE image using the motion information, generating a pixel-weight coefficient for each of the SE image, the LE image, and the AE image, generating an overlapped region mask corresponding to an overlapped region in each of the SE image, the LE image and the LE image, determining a modified pixel-weight coefficient in the overlapped region mask and correcting a brightness difference, and generating an HDR image from the SE image, the LE image and the AE image using the modified at least one pixel-weight coefficient.

Method and apparatus for generating HDR images

A method of selecting capture configuration based on scene analysis and an image capturing device are provided. The method includes analyzing by a processor, a scene currently being captured by an image capturing device having a plurality of imaging sensors, identifying a current image capturing mode of the image capturing device, setting at least one capture parameter for the plurality of the imaging sensors, upon determining that the at least one capture parameter of the current image capturing mode has to be changed, and determining a timing sequence for triggering the plurality of imaging sensors to capture a plurality of image frames based on the set at least one capture parameter.

Method and apparatus for selecting capture configuration based on scene analysis

A method and an electronic device for producing a composite image are provided. The method includes receiving visible image data and near infrared (NIR) image data from a composite sensor, determining whether at least one portion of the NIR image data having a level of detail greater than or equal to a threshold, and generating a composite image by fusing the visible image data with the at least one portion of the NIR image data based on the determination and storing the composite image in a memory.

Method and electronic device for producing composite image

A system for calibrating a thermal camera with a calibration target. The calibration target may have a pattern which can be seen on an infrared image captured by the camera. The pattern may be of various kinds. For example, the pattern may be a checkerboard with some, such as every other square, having one emissitivity and the remaining squares having a different emissitivity, or having infrared light sources placed at corners of the squares. A difference between the emmissitivities may be sufficient so that the checkerboard pattern appears in an infrared image captured by the camera for calibration. The calibration may aid in determining intrinsic and extrinsic parameters of the camera. The parameters may provide a basis for transforming camera pixel coordinates to a world coordinate system which allows measurement of real world entities by the thermal camera. Measurements may incorporate distances between objects, heights of objects, and so forth.

Thermal camera calibration

A method and system () are provided for monitoring a restricted area () below a temporarily elevated worker () working on an elevated power transmission line (). The method and system () utilize a video camera system () that is temporarily elevated to a location () adjacent the worker () and that is configured to detect the presence of personnel () who enter the restricted area (). The system () is configured to automatically alert personnel () at the worksite () who enter the restricted area () in response to detection of the personnel () by the system ().

System and method for video monitoring of restricted areas below bucket trucks, lineworkers on power distribution poles or other elevated loads

A method comprises receiving an image of the area, the image representing the area in a first color space; converting the received image to at least one second color space to produce a plurality of converted images, each converted image corresponding to one of a plurality of color sub-spaces in the at least one second color space; calculating upper and lower thresholds for at least two of the plurality of color sub-spaces; applying the calculated upper and lower thresholds to the converted images corresponding to the at least two color sub-spaces to segment the corresponding converted images; fusing the segmented converted images corresponding to the at least two color sub-spaces to segment the received image; and updating the segmentation of the received image based on edge density data in the received image.

System and method for obstacle detection using fusion of color space information

A speech recognition system and a personal speech profile data (PSPD) storage device that is physically distinct from the speech recognition system are provided. In the speech recognition system, a PSPD interface receives voice training data, which is associated with an individual and the operating conditions of an aircraft, from the PSPD storage device. A speech input module produces a digital speech signal derived from an utterance made by a system user. A speech processing module accesses voice training data stored on the PSPD storage device through the PSPD interface, and executes a speech processing algorithm that analyzes the digital speech signal using the voice training data, in order to identify one or more recognized terms from the digital speech signal. A command processing module initiates execution of various applications based on the recognized terms. Embodiments may be implemented in various types of host systems, including an aircraft cockpit-based system.

Aircraft speech recognition and voice training data storage and retrieval methods and apparatus

A rate of change of visual content (compared to an adjacent video frame) of a video frame is determined, and the video frame is selected as a key video frame if the rate exceeds a threshold value. In an embodiment, to compute the rate, the motion energy vector magnitude (square of displacement magnitude) of each moved pixel of the current frame is determined, and an average displacement magnitude is determined. The average displacement magnitude may also be used to determine the rate.

Identifying key video frames

A method for the detection of motion in video data is disclosed. In an embodiment, a method uses a background technique for the motion detection. In another embodiment, a Gaussian Mixture Model is applied to a neighborhood or block of pixels within an image frame, thereby identifying background and foreground in the image based on said blocks.

Block-based Gaussian mixture model video motion detection

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Bengaluru, India

Lokesh Rayasandra Boregowda