Samsung Electronics Co., Ltd.

Thinkware Corporation

Hyundai Motor Company

Kia Motors Corporation

Corning Precision Materials Co., Ltd.

Other

Sk Chemicals Co., Ltd.

Shin Hyoung Kim

Jung Gyun Han

Sang Sik Yoon

Hyeon Cheol Kim

Ki Hwan Kwon

Hyun Ju Lee

Jea Yun So

See Hyun Kim

Yun Soo Jang

Do Kyung Lee

In Gyu Choi

Seung Ryong Cha

Dong Hun Lee

Tae Kyu Han

Won Min Lee

Hyun Soo Jung

Byoung In Lee

Hye Kyung Byun

Ki Wook Lee

Yeon Kyu Jeong

Sang Hwa Choi

Sung Jin Park

Dong Min Shin

Heum Yong Park

Kyung Shik Roh

Chang Hyun Lee

Byung Chan Kim

Jae Youl Jeong

Gwang Jin Jung

Yeonho Kim

Suk June Yoon

Jun Young Lee

Wan Ho Kim

Ji Min Kim

Jae Young Jung

Kyoung Min Koh

Suk Pil Ko

Donghun Lee

Jae-Phil Boo

Kyungha Kim

No San Kwak

Kyung-shik Roh

Young Ho Ko

Kyung Han Jeong

Tal Chol Kim

Jae Jin Jung

Tae Soo Kim

Sungjin Park

Seung-Jae Lee

Dong Hyun Lee

Dong-Hyun Lee

Jae Young Choi

Yong-Seok Kim

Min Sung Kim

Jong Yun Park

Jong Hyun Kim

Yongseok Kim

Tae-Hun Kim

Sang Jin Park

Seung Jin Lee

Min Jae Kim

Hyun Jung Lee

Jun Pyo Hong

Jae-min Lee

Hyeon Koon Myeong

Sang Jin Hyun

Young Do Kwon

Jeong Hwan Kim

Kwang Hyun Lee

In-seak Hwang

Dongmin Shin

Jang Mi Lee

Han Vit Yang

Yong Kyun Lim

Ju Young Lee

Ki Nam Kim

Hyun-ju Lee

Tae-Gyeong Chung

Bong-Yong Lee

Nam-Seog Kim

Ji-Min Kim

Byeol Teo Park

Kyung Ha Kim

Jeong Gon Song

Seung Jae Kang

Dong Woo Ha

Won Seok Song

Keun Ryu

Soon Yong Park

Nam Ho Kim

Seungwoo Seo

Jin-Hyuk Lee

Kyoung-Moon Kang

Jae Cheol Yun

Sung Il You

Byoung Hoon Choi

Ji Eun Park

Woong Joo

Woo-Dong Lee

Tae Won Kim

An augmented reality (AR)-based route guidance method includes acquiring a driving image captured by an image capturing device of a vehicle which is running, acquiring route data to a destination of the vehicle, recognizing both side lane markings of a lane in which the vehicle is running from the acquired driving image, generating first route guidance linear data based on the recognized both side lane markings for a region in which both side lane markings are recognized in the driving image, generating second route guidance linear data using link linear data of the route data for a region in which both side lane markings are not recognized in the driving image, combining the first route guidance linear data and the second route guidance linear data to generate combined route guidance linear data, and displaying a route guidance object in AR using the generated combined route guidance linear data.

AR processing device, augmented reality-based route guidance method and electronic device

A cleaning apparatus including a vacuum cleaner and a docking station is provided. The cleaning apparatus includes a vacuum cleaner including a dust collecting chamber in which foreign substances are collected, and a docking station configured to be connected to the dust collecting chamber to remove the foreign substances collected in the dust collecting chamber. The dust collecting chamber is configured to collect foreign substances through centrifugation, and configured to be docked to the docking station, and the docking station includes a suction device configured to suction the foreign substances and air in the dust collecting chamber docked to the docking station.

Cleaning apparatus having vacuum cleaner and docking station

Disclosed is an image processing method. The method includes the steps of receiving an image obtained from a plurality of vehicles positioned on a road, storing the received images according to acquisition information of the received images; determining a reference image and a target image based on images having the same acquisition information among the stored images, performing an image registration using a plurality of feature points extracted from each of the determined reference image and target image, performing a transparency process for each of the reference image and the target image performed with the image registration, extracting static objects from the transparency-processed image, and comparing the extracted static objects with objects on an electronic map pre-stored to updating the electronic map data, when the objects on the electronic map data pre-stored are different from the extracted static objects.

Image processing apparatus, image processing method, computer program and computer readable recording medium

There is provided a method for detecting a vehicle including receiving continuously captured front images, setting a search area of the vehicle in a target image based on a location of the vehicle or a vehicle area detected from a previous image among the front images, detecting the vehicle in the search area according to a machine learning model, and tracking the vehicle in the target image by using feature points of the vehicle extracted from the previous image according to a vehicle detection result based on the machine learning model. Since the entire image is not used as a vehicle detection area, a processing speed may be increased, and a forward vehicle tracked in an augmented reality navigation may be continuously displayed without interruption, thereby providing a stable service to the user.

Method for detecting vehicle and device for executing the same

A cleaning robot and a method of controlling the same, the cleaning robot performing docking by detecting light emitted from a docking station using a Lidar sensor or a light receiving element separately provided on a printed circuit board (PCB) of the Lidar sensor, and performing docking based on the number of light emitting elements of the docking station identified according to the detected light are provided. The cleaning robot includes a main body, a drive unit configured to move the main body, a Lidar sensor including a Lidar optical transmitter, a Lidar optical receiver, and the PCB to which the Lidar optical transmitter and the Lidar optical receiver are fixed and provided to be rotatable, a docking optical receiver fixed to the PCB and configured to receive light emitted from the docking optical transmitter of the docking station, and at least one processor is configured to control the drive unit to be docked on the docking station based on light received by the docking optical receiver.

Cleaning robot and controlling method thereof

A method for measuring an inter-vehicle distance includes acquiring a driving image photographed by a photographing device of a first vehicle which is being driven; detecting a second vehicle from the acquired driving image; detecting first feature points of a second vehicle region in a first frame corresponding to a frame in which the second frame is detected before a frame in which the second vehicle is not detected among a plurality of frames constituting the driving image, when the second vehicle is not detected from the driving image; detecting second feature points in a second frame corresponding to a current frame by tracking the detected first feature points; calculating a feature point change value between the first feature points and the second feature points; and calculating an inter-vehicle distance from the photographing device of the first vehicle to the second vehicle based on the calculated feature point change value.

Method, apparatus, electronic device, computer program, and computer readable recording medium for measuring inter-vehicle distance based on vehicle image

A robot vacuum cleaner is provided. The robot vacuum cleaner includes a camera, a memory configured to store an artificial intelligence model trained to identify an image from an input image and shape information corresponding to each of a plurality of objects, and a processor configured to control the electronic apparatus by being connected to the camera and the memory, wherein the processor is configured to input an image obtained by the camera to the artificial intelligence model to identify an object included in the image, obtain shape information corresponding to the identified object among the plurality of shape information stored in the memory, and set a traveling path of the robot vacuum cleaner based on the shape information and size information related to the object.

Electronic apparatus and method of controlling thereof

Disclosed is a cyclone dust collector in which usability is improved. A vacuum cleaner comprising a cyclone dust collector, wherein the cyclone dust collector includes, a case configured to swirl suctioned air to separate dust from the suctioned air and accommodate the separated dust, a grill assembly separably installed in the case, and a cleaning portion included in the case and configured to remove dust adhered to a surface of the grill assembly when the grill assembly is separated from the case.

Cyclone dust collector and vacuum cleaner having the same

A method for measuring an inter-vehicle distance using a processor is provided. The method includes acquiring a driving image photographed by a photographing device of a first vehicle; detecting a second vehicle from the driving image and calculating a ratio between an image width of the detected second vehicle and an image width of a lane in which the second vehicle is located; determining a size class of the second vehicle among a plurality of size classes based on the calculated ratio; determining a width of the second vehicle based on the determined size class of the second vehicle; and calculating a distance from the photographing device to the second vehicle based on the determined width of the second vehicle, a focal length of the photographing device, and the image width of the second vehicle.

Method, apparatus, electronic device, computer program and computer readable recording medium for measuring inter-vehicle distance using driving image

Growing community of inventors

Gyeonggi-do, South Korea

Shin Hyoung Kim