Hanwha Techwin Co., Ltd.

Seoul National University

Hanwha Aerospace Co., Ltd.

Hanwha Land Systems Co., Ltd.

Jeong Eun Lim

Seung In Noh

Dong Jun Park

Jin Young Choi

Se Mi Jang

Jik Han Jung

Young Joon Yoo

Ho Jung Lee

Kwang Moo Yi

Young Min Baek

Ji Sung Kim

Seoung Seon Jeon

Ha Wook Jeong

An event search device includes: a first communication unit configured to receive, from a camera, a plurality of image frames of a surveillance area generated in response to an occurrence of an event; and metadata including time information of the occurrence of the event and location information of an event in the image frames; a user interface configured to receive a search condition for searching for the event, the search condition including an event search area; a screen unit configured to display the event search area on the image frames; and a control unit configured to search for an event satisfying the search condition within the event search area by using the metadata, wherein at least one of a location, a size, and a shape of the event search area is defined through the user interface.

Event search system, device, and method

A system and method for providing surveillance data are provided. The system includes: a pattern learner configured to learn a time-based data pattern by analyzing at least one of image data of one or more images and sound data of sound obtained from a surveillance zone at a predetermined time or time period, and to generate an event model based on the time-based data pattern; and an event detector configured to detect at least one event by comparing the event model with a time-based data pattern of at least one of first image data of one or more first images and first sound data of first sound obtained from the surveillance zone.

System and method for providing surveillance data

The present invention relates to an event searching apparatus comprising: a communication interface configured to receive, from a camera, a plurality of image frames obtained by photographing a surveillance region and metadata comprising time information of occurrence of an event and location information regarding a location of the occurrence of the event; a search map generator configured to generate a search map corresponding to the image frames and comprising a plurality of blocks; a time stamp setter configured to set at least one time stamp comprising the time information in at least one block, corresponding to the location information; a user interface configured to receive a search location as a search condition for an event search in the surveillance region; and an event searcher configured to search for and find a time stamp included in a block near the search location among the blocks, and perform event search using metadata regarding an image frame indicated by the found time stamp.

Event searching apparatus and system

Provided are a motion detection system and method. The motion detection system includes a pixel-based detector configured to compare a previous frame and a present frame to extract pixel constituting a first foreground region, a region-based detector configured to extract a second foreground region based on peripheral pixels of a pixel to be inspected, and a motion determiner configured to detect, as a final motion region among pixel groups of the first foreground region, a pixel group comprising pixels corresponding to the second foreground region.

Motion detection system and method

Provided is a video search system and method. The video search system includes: a search engine configured to extract video data matching a search condition from an original video; and a browsing engine configured to generate a summarized video based on the extracted video data, render a plurality of objects in the summarized video on a background model in an overlapping manner in an object appearing order in the original video, and display the rendered objects.

Video search system and method

Provided are a method and apparatus for detecting an abnormal movement. The apparatus includes a feature tracing unit configured to extract features of a moving object in an input image, trace a variation in position of the extracted features according to time, and ascertain trajectories of the extracted features; a topic online learning unit configured to classify the input image in units of documents which are bundles of the trajectories, and ascertain probability distribution states of topics, which constitute the classified document, by using an online learning method which is a probabilistic topic model; and a movement pattern online learning unit configured to learn a velocity and a direction for each of the ascertained topics, and learn a movement pattern by inferring a spatiotemporal correlation between the ascertained topics.

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Changwon-si, South Korea

Jeong Eun Lim