Samsung Electronics Co., Ltd.

Sudha Velusamy

Anshul Sharma

Aniket Devdatta Rege

Kihuk Lee

Gaurav Jain

Girish R Kulkarni

Swadha Jaiswal

Ravi Prasad Mohan Kini

Rahul Varna

Sunho Moon

Viswanath Gopalakrishnan

Karthikeyan Somanathan

Cheolyong Jeon

Balasubramanian Anand

Uison Yoon

Hariprasad Kannan

Girish Kulkarni

Sachin Dev

Daeyoung Hyun

Bilva Bhalachandra Navathe

Yeonjong Bong

Jehan Yoon

Rishubh Parihar

Ramakrishnan Srinivasakannan

Gaurav Ramola

Pradeep Kumar Vegireddi

Nikhar Maheshwari

Sai Pranav Mathivanan

Embodiments herein provide a method for detecting a candid moment in an image frame. The method includes: receiving, by an electronic device, image frames; determining, by the electronic device, a candid score of each image frame in the image frames using a Machine Learning (ML) model, wherein the candid score is a quantitative value of candidness present in the image frames; determining, by the electronic device, whether the candid score of the image frame in the image frames meets a threshold candid score; identifying, by the electronic device, that the candid moment is present in the image frame in response to determining that the candid score of the image frame meets the threshold candid score; and displaying, by the electronic device, the image frame comprising the candid moment.

Method and electronic device for detecting candid moment in image frame

A device and method are provided for providing a function related to a camera in an electronic device. The electronic device includes a display device; a first camera; a processor; and a memory configured to store instructions, which when executed, instruct the processor to acquire a plurality of first images having a first attribute and one or more second images having a second attribute through the first camera for a predetermined time, when an input associated with image acquisition is received, generate one or more image content based on the plurality of first images or the one or more second images, and store instructions that cause the one or more image content to be output through the display device.

Electronic device including camera and method of operating the same

A method includes determining information indicative of at least one facial characteristic associated with at least one face in the source image, processing the source image using a filter based on the determined information, performing wavelet decomposition on each of the filtered image and the source image, determining weightage factors associated with the wavelet decomposition of each of the filtered image and the source image, based on the determined information, obtaining a wavelet image to generate a texture restored image from the wavelet decomposition of each of the filtered image and the source image based on the weightage factors.

Method and electronic device for processing facial images

A method and system for detecting temporal segments of talking faces in a video sequence using visual cues. The system detects talking segments by classifying talking and non-talking segments in a sequence of image frames using visual cues. The present disclosure detects temporal segments of talking faces in video sequences by first localizing face, eyes, and hence, a mouth region. Then, the localized mouth regions across the video frames are encoded in terms of integrated gradient histogram (IGH) of visual features and quantified using evaluated entropy of the IGH. The time series data of entropy values from each frame is further clustered using online temporal segmentation (K-Means clustering) algorithm to distinguish talking mouth patterns from other mouth movements. Such segmented time series data is then used to enhance the emotion recognition system.

Method and apparatus for detecting talking segments in a video sequence using visual cues

An apparatus and method are provided for recognizing an emotion of an individual based on Action Units. The method includes receiving an input AU string including one or more AUs that represents a facial expression of an individual from an AU detector; matching the input AU string with each of a plurality of AU strings, wherein each of the plurality of AU strings includes a set of highly discriminative AUs, each representing an emotion; identifying an AU string from the plurality of AU strings that best matches the input AU string; and outputting an emotion label corresponding to the best matching AU string that indicates the emotion of the individual.

Method and apparatus for recognizing an emotion of an individual based on facial action units

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Bengaluru, India

Sudha Velusamy