Samsung Electronics Co., Ltd.

Viswanath Gopalakrishnan

Kiran Nanjunda Iyer

Raushan Kumar

Satish Lokkoju

Sudha Velusamy

Viswanath Veera

Anshul Sharma

Kapil Soni

Biplab Chandra Das

Bilva Bhalachandra Navathe

A method and an electronic device for displaying images in a multi-dimensional mode based on personalized topics are provided. The method includes generating a plurality of personalized topics based on a plurality of images stored in the electronic device across a predetermined time period, and displaying the plurality of personalized topics along a timeline.

Method of displaying images in a multi-dimensional mode based on personalized topics

A method, which facilitates interaction with virtual reality device, includes receiving a user input via a wearable device; extracting a parameter and a value of the parameter from the user input; transmitting the parameter and the value of the parameter to the VR device; identifying an action corresponding to the parameter and the value; and executing the action.

Method and apparatus for facilitating interaction with virtual reality equipment

The present disclosure relates to image retrieval in an electronic device. An operating method of an electronic device includes determining an object included in an image and a position of extent occupied by the object in the image and retrieving at least one image including the object at the position from among a plurality of images.

Method for retrieving image and electronic device thereof

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.

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Bengaluru, India

Viswanath Gopalakrishnan