Samsung Electronics Co., Ltd.

Korea Institute of Science and Technology

Beijing Samsung Telecom R&d Center

Kyoobin Lee

Keun Woo Park

Jun Haeng Lee

Hyun Surk Ryu

Eric Hyunsurk Ryu

Jooyeon Woo

Chang-Woo Shin

Qiang Wang

Ping Guo

Yibing Michelle Wang

Ilia Ovsiannikov

Jun Seok Kim

Shandong Wang

Zhengping Ji

Qiang Zhang

Wentao Mao

Xiaotao Wang

Guangqi Shao

Kyoungseok Pyun

So Young Lee

Chang Kyu Choi

Qing Fa Wang

Jia Qi Li

Sunghoon Hong

Joon Ah Park

Feng Shi

Keun Joo Park

Changwoo Shin

Hee Sup Shin

Tobi Delbruck

Yeon-Soo Kim

Chang Woo Shin

Seung-Chan Kim

Eunji Cheong

Hee-sup Shin

Wei H Liu

Jungryun Lee

Joo Yeon Woo

Sukchan Lee

EricHyunsurk Ryu

Eric Hyun-surk Ryu

Sang-Gyun Chon

Raphael Berner

Ji In Baek

Yihong Zheng

Seongwook Kim

Maryam Sanati

Sukyung Lee

Ilhwan Choe

Jing Tao Xu

Dong Qing Zou

Hyun Suk Ryu

De Heng Qian

Hongpyo Kim

Ryu Erichyunsurk

A method and device for recognizing a motion of an object, the method including receiving event signals from a vision sensor configured to sense the motion, storing, in an event map, first time information indicating a time at which intensity of light corresponding to the event signals changes; generating an image based on second time information corresponding to a predetermined time range among the first time information, and recognizing the motion of the object based on the image.

Method and device for recognizing motion

An apparatus for use interface and a method of user interface are provided. The apparatus may include a classifier configured to classify an event as corresponding to a class among at least two classes, an updater configured to update class information related to the class corresponding to the event, and a processor configured to determine a user input corresponding to the event based on the updated class information.

Apparatus and method of using events for user interface

An apparatus for providing a user interface provides a first user interface mode, and can switch to a second user interface mode if it receives a user command instructing to switch the mode to the second user interface mode which has a different user command input method from the first user interface mode. In the switching process, the apparatus is configured to reset a recognition pattern to distinguish a smaller number of user input types than the number of the user input types distinguishable in the first UI mode.

Apparatus and method for providing user interface

Embodiments of the present invention provide a method and device for processing Dynamic Vision Sensor (DVS) events. The method comprises the operations of: acquiring a DVS event map sequence; for any DVS event map in the DVS event map sequence, extracting a DVS event feature descriptor, where the DVS event feature descriptor has a scale-invariant feature and/or a rotation-invariant feature; determining, according to the extracted DVS event feature descriptor, a three-dimensional space pose of the DVS event map at the current moment; and, generating, according to the three-dimensional space pose of each DVS event map, a DVS event map sequence with temporal consistency. The embodiments of the present invention are used for generating, from a DVS event map sequence, a DVS event map sequence with temporal consistency.

Method and device for processing DVS events

A device and method to display a screen based on an event are provided. A device according to an exemplary embodiment may display, in response to an event associated with a movement of an object, a graphic representation that corresponds to the event by overlaying the graphic representation on visual contents.

Device and method for displaying screen based on event

A modeling method using a three-dimensional (3D) point cloud, the modeling method including extracting at least one region from an image captured by a camera; receiving pose information of the camera based on two-dimensional (2D) feature points extracted from the image; estimating first depth information of the image based on the at least one region and the pose information of the camera; and generating a 3D point cloud to model a map corresponding to the image based on the first depth information.

Modeling method and apparatus using three-dimensional (3D) point cloud

An apparatus and a method. The apparatus includes a dynamic vision sensor (DVS) configured to generate a stream of events, where an event includes a location and a binary value indicating a positive or a negative change in luminance; a sampling unit connected to the DVS and configured to sample the stream of events; and an image formation unit connected to the sampling unit and configured to form an image for each sample of the stream of events, wherein a manner of sampling by the sampling unit is adjusted to reduce variations between images formed by the image formation unit.

Method and apparatus for event sampling of dynamic vision sensor on image formation

A pose estimation method and apparatus are provided. The method includes determining, as a rotation component, an output value of a motion sensor configured to sense a motion of the pose estimation apparatus, determining a change amount of a translation component based on the rotation component, and the translation component extracted from images photographed by a vision sensor included in the pose estimation apparatus, optimizing the translation component based on the change amount, and outputting the rotation component and the optimized translation components a pose estimation value of the pose estimation apparatus.

Pose estimation method and apparatus

An object recognition apparatus and an object recognition method are provided. The object recognition method includes generating an input image based on an event flow of an object, generating a composite feature based on features extracted by a plurality of recognizers, and recognizing the object based on the composite feature.

Object recognition method and apparatus

An image generating method and an image generating apparatus are provided. The image generating method includes generating a first image based on first event signals that are output from an event-based vision sensor during a first time period and stored in a buffer, generating a second image based on second event signals that are output from the event-based vision sensor during a second time period and stored in the buffer, and aligning the first image and the second image to generate a third image having a quality that is higher than qualities of the first image and the second image.

Image generating method and apparatus

An image deblurring method and an image deblurring apparatus are provided. The image deblurring method includes acquiring a blurred image and a dynamic vision sensor (DVS) event set that is recorded by a DVS while the blurred image is exposed, and deblurring the blurred image, based on the DVS event set.

Image deblurring method and apparatus

A user input processing method is provided. The user input processing method determines, based on a recognition reliability of a user input for a function, a delay time and whether the function is to be performed, the function being determined in advance, and controls the function based on the delay time and whether the function is to be performed.

Method and apparatus for processing user input

A method and apparatus for detecting an object using an event-based sensor is provided. An object detection method includes determining a feature vector based on target pixels and neighbor pixels included in an event image, and determining a target object corresponding to the target pixels based on the feature vector.

Method and apparatus of detecting object using event-based sensor

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Seoul, South Korea

Kyoobin Lee