Samsung Electronics Co., Ltd.

Omnissa, LLC

Anshul Sharma

Sudha Velusamy

Arun George

Rajesh Krishnan

Gourav Mukherjee

Viswanath Gopalakrishnan

Jagjit Singh Sethi

Balasubramanian Anand

Hariprasad Kannan

Bilva Bhalachandra Navathe

Vishak G

Nikolay Poturnak

Disclosed are various approaches for providing touchless visitor management. A visitor can complete a visitor registration process using a client device of the visitor and obtain a virtual badge credential to a visitor's device. A physical access control system credential as well as a visitor badge can also be obtained to the visitor's device.

Day zero user access to enterprise resources

A method for converting an electronic flash storage device having a byte addressable storage (ByAS) and a block addressable flash storage (BlAS) to a single byte addressable storage includes receiving, by a host, a request for memory allocation from the ByAS, the receiving being from a first application among of a plurality of applications running on a processor; deallocating, by the host, a least relevant page allocated to at least one second application among the plurality of applications; moving, by the host, a content to the BlAS at a first BlAS location, the content related to the least relevant page, the moving based on the deallocation; allocating, by the host, the least relevant page to the first application; and updating, by the host, a cache metadata and a page lookup table of the first application and the at least one second application based on the deallocation and allocation.

Method and system for converting electronic flash storage device to byte-addressable nonvolatile memory module

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

Anshul Sharma