Samsung Electronics Co., Ltd.

Huawei Technologies Co., Limited

Maolin Chen

Fan Zhang

Rong Liu

Ji Yeun Kim

Xun Sun

Lujin Gong

Zhilan Hu

Moon-Sik Jeon

Chang Kyu Choi

Wei Zhang

Chen Wang

Young-su Moon

Kee Chang Lee

Bo Bai

Jun-mo Kim

Seokcheol Kee

Shuang Yang

Lijun Luo

Yuhao Jiang

Moon Sik Jeong

Qiankun You

Xianbo Mou

Guangming Guo

Lihu Xiao

Luping Li

A target detection method and apparatus, in which the method includes: obtaining a target candidate region in a to-be-detected image; determining at least two part candidate regions from the target candidate region by using an image segmentation network, where each part candidate region corresponds to one part of a to-be-detected target; and extracting, from the to-be-detected image, local image features corresponding to the part candidate regions; and learning the local image features of the part candidate regions by using a bidirectional long short-term memory LSTM network, to obtain a part relationship feature used to describe a relationship between the part candidate regions; and detecting the to-be-detected target in the to-be-detected image based on the part relationship feature. As a result, image data processing precision in target detection can be improved, application scenarios of target detection can be diversified, and target detection accuracy can be improved.

Target detection method, apparatus, and system

An image query method and apparatus, where the method may include obtaining a global feature of a query image and an attributive feature of the query image, where the attributive feature is a feature used to describe a specific attribute area in the query image, querying an image library using the global feature to obtain a first image set that includes at least one image, where an image included in the image library includes the attributive feature, selecting at least one image whose similarity of the attributive feature to the attributive feature of the query image is greater than a preset threshold from the first image set, and setting the at least one selected image as a second image set. Hence, the method may improve image query efficiency.

Image query method and apparatus

A pedestrian retrieval method and apparatus that belong to the video surveillance field include extracting first feature data, second feature data, and third feature data of a target pedestrian image, where the target pedestrian image is an image of a to-be-retrieved pedestrian, and the first feature data, the second feature data, and the third feature data respectively include a plurality of pieces of body multidimensional feature data, a plurality of pieces of upper-body multidimensional feature data, and a plurality of pieces of lower-body multidimensional feature data of the target pedestrian image, screening stored multidimensional feature data based on the first feature data, the second feature data, and the third feature data to obtain a target feature data set, and outputting a pedestrian retrieval result using the target feature data set.

Pedestrian retrieval method and apparatus

Provided is an image surveillance method and apparatus. The image surveillance method includes photographing a predetermined place and generating an image signal corresponding to the predetermined place, detecting a change in the image signal by calculating a difference between a current frame and a previous frame of the generated image signal, and generating alarm information corresponding to the detected change in the image signal in order to alarm a user.

Portable terminal having video surveillance apparatus, video surveillance method using the portable terminal, and video surveillance system

An apparatus for detecting a body part from a user image may include an image acquirer to acquire a depth image, an extractor to extract the user image from a foreground of the acquired depth image, and a body part detector to detect the body part from the user image, using a classifier trained based on at least one of a single-user image sample and a multi-user image sample. The single-user image may be an image representing non-overlapping users, and the multi-user image may be an image representing overlapping users.

Apparatus and method for detecting body parts from user image

Provided is a device and method for estimating a head pose which may obtain an excellent head pose recognition result free from the influence of an illumination change, the device including a head area extracting unit to extract a head area from an input depth image, a head pitch angle estimating unit to estimate a pitch angle of a head in the head area, a head yaw angle estimating unit to estimate a yaw angle of the head in the head area, and a head pose displaying unit to display a head pose based on the estimated pitch angle of the head and the estimated yaw angle of the head.

Device and method for estimating head pose

Disclosed are an apparatus and a method of detecting a human component from an input image. The apparatus includes a training database (DB) to store positive and negative samples of a human component, an image processor to calculate a difference image for the input image, a sub-window processor to extract a feature population from a difference image that is calculated by the image processor for the positive and negative samples of a predetermined human component stored in the training DB, and a human classifier to detect a human component corresponding to a human component model using the human component model that is learned from the feature population.

Detecting apparatus of human component and method thereof

An apparatus and method for parsing a human body image may be implemented by acquiring a depth image including a human body, and detecting a plurality of points in the acquired depth image by conducting a minimum energy skeleton scan on the depth image.

Apparatus and method for parsing human body image

A device and a method for image processing include an image processing device that may extract a foreground moving object from a depth map of a three-dimensional (3D) image that may include an image depth map acquirer to obtain the depth map of a successive 3D image over a period of time, a moving object segmenter to segment a moving object from the obtained depth map, and a moving object tracker to identify and track the segmented moving object.

Device and method for image processing

Provided is a target analysis apparatus, method and computer-readable medium based on a depth image and an intensity image of a target is provided. The target analysis apparatus may include a body detection unit to detect a body of the target from the intensity image of the target, a foreground segmentation unit to calculate an intensity threshold value in accordance with intensity values from the detected body, to transform the intensity image into a binary image using the intensity threshold value, and to mask the depth image of the target using the binary image as a mask to thereby obtain a masked depth image, and an active portion detection unit to detect an active portion of the body of the target from the masked depth image.

Target analysis apparatus, method and computer-readable medium

Provided are an apparatus and method of extracting a discriminative color feature, and an image forming system including: a photographing device to photograph an image of an object; a color feature extracting device receiving the image from the photographing device, extracting a discriminative color feature from the image, generating a final color model of the object, extracting a color blob of the object based on the final color model, performing blob analysis on the extracted color blob, and generating parameters to control a posturing of the photographing device according to the blob analysis; a control device receiving from the color feature extracting device the parameters to control the posturing of the photographing device, and controlling the posturing of the photographing device; a storage device storing the photographed image of the object; and a display device displaying the photographed image of the object.

Image forming system, apparatus and method of discriminative color features extraction thereof

An apparatus and method for detecting a head image of an input image. In the head image detection apparatus, a training DB stores therein a positive head image and a negative head image into which a plurality of images are classified. A sub-window processor extracts a feature population while sliding a sub-window of a predetermined size with respect to the input image. A head candidate region classifier classifies head candidate regions based on the extracted feature population from the sub-window processor by referring to samples stored in the training DB. A head candidate region determiner determines a head candidate region as a head region by checking continuity of contours of the classified head candidate regions.

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Beijing, China

Maolin Chen