Sony Corporation

Sony (china) Limited

Chinese Academy of Sciences

Weiguo Wu

Takayuki Yoshigahara

Liang Li

Bo Han

Yuyu Liu

Kun Liu

Atsushi Yokoyama

Long Meng

Yoshiaki Iwai

Keisuke Yamaoka

Akira Nakamura

Hiroyuki Sato

Lun Zhang

Yonghong Yan

Teruyuki Ushiro

Qingwei Zhao

Li Lu

Li Liang

Yichuan Hu

Yuwei Li

Hongbin Suo

Shiqu Mei

The invention discloses a mobile terminal, comprising a display unit configured to display an image to be displayed in three-dimensional space beyond the mobile terminal, a determination module configured to determine an instruction input by a user through the displayed image via spatial position detection, and a processing module configured to execute an operation corresponding to the determined instruction. In the invention, both the display of the image in the three-dimensional space beyond the mobile terminal and the spatial position detection are beneficial to execute the operation corresponding to the instruction from the user accurately, so that the user can observe the image conveniently, the limitation of a screen size is eliminated, the instruction from the user can be judged and executed accurately, and user experience is improved.

Three dimensional user interface for watch device

An object recognizing apparatus and method are provided. The apparatus may include: a viewing direction estimating device configured for respectively estimating a first viewing direction of a first object captured by a first camera and a second viewing direction of a second object captured by a second camera; a feature extracting device configured for extracting one or more features respectively from an image containing the first object captured by the first camera and an image containing the second object captured by the second camera; and an object matching device configured for allocating a weight for each of the one or more features according to the first viewing direction and the second viewing direction, and calculating a similarity between the first object and the second object based on the one or more weighted features, to determine whether the first object and the second object are the same object.

Object recognizing apparatus and method

This invention relates to retrieval for multimedia content, and provides a program endpoint time detection apparatus for detecting an endpoint time of a program by performing processing on audio signals of said program, comprising an audio classification unit for classifying said audio signals into a speech signal portion and a non-speech signal portion; a keyword retrieval unit for retrieving, as a candidate endpoint keyword, an endpoint keyword indicating start or end of the program from said speech signal portion; a content analysis unit for performing content analysis on context of the candidate endpoint keyword retrieved by the keyword retrieval unit to determine whether the candidate endpoint keyword is a valid endpoint keyword; and a program endpoint time determination unit for performing statistics analysis based on the retrieval result of said keyword retrieval unit and the determination result of said content analysis unit, and determining the endpoint time of the program. In addition, this invention also provides a program information retrieval system. With present invention, program information regarding a program attended by user can be rapidly obtained.

Program endpoint time detection apparatus and method, and program information retrieval system

The present invention provides a device and method for multiclass object detection, wherein the detection device includes: an input unit configured to input data to be detected; and a joint classifier within which a plurality of strong classifiers capable of processing multiclass object data are included, wherein each of the strong classifiers is acquired by adding a set of weak classifiers together, and each weak classifiers performs a weak classification for the data to be detected by using a feature. A list of shared features is included within the joint classifier, and each feature within the list is shared by one or more weak classifiers belonging to different strong classifiers respectively; and the weak classifiers, which use a same feature and belong to different strong classifiers respectively, have different parameter values from one another.

Device and method for multiclass object detection

The present invention discloses a three dimensional human pose recognition method and apparatus, where the three dimensional human pose recognition method includes steps of: a three dimensional pose initial recognition step of performing three dimensional pose recognition on an input image containing a human image to obtain image-based three dimensional human pose information; a sensor information acquisition step of acquiring, by a motion sensor, motion information of human articulation points; and a three dimensional pose correction step of correcting, with the motion information acquired by the sensor information acquisition step, the image-based three dimensional human pose information recognized by the three dimensional pose initial recognition step. According to the technical solution of the invention, it is possible to improve accuracy of the three dimensional human pose recognition efficiently. Further, the present invention also discloses a three dimensional human pose recognition method and apparatus, in which three dimensional half-body pose recognition is proposed, thereby speed of three dimensional human pose recognition can be improved significantly while improving accuracy of three dimensional human pose recognition.

Three dimensional human pose recognition method and apparatus

Provided are a method and device for determining a lean angle of a body and a pose estimation method and device. The method for determining a lean angle of a body of the present invention includes: a head-position obtaining step for obtaining a position of a head; a search region determination step for determining a plurality of search region spaced with an angle around the head; an energy function calculating step for calculating a value of an energy function for the search region; and a lean angle determining step for determining the lean angle of a search region with a largest or smallest value of the energy function as the lean angle of the body. The pose estimation method of the present invention includes a body lean-angle obtaining step, for obtaining a lean angle of a body; and a pose estimation step, for performing a pose estimation based on the lean angle of the body.

Method and device for determining lean angle of body and pose estimation method and device

A method and apparatus that classify an image. The method extracts a feature vector from the image, wherein the feature vector includes a plurality of first features. The extracting of each of the first features includes: acquiring a difference between sums or mean values of pixels of the plurality of first areas in the corresponding combination to obtain a first difference vector in the direction of the first axis, and obtaining a second difference vector in the direction of the second axis. A first projection difference vector is acquired with a second projection difference vector. A sum of magnitudes of the first projection difference vector and the second projection difference vector as the first feature is obtained; and the image according to the extracted feature vector is classified.

Method of and apparatus for classifying image

The present invention discloses a method and an apparatus for extracting a prosodic feature of a speech signal, the method including: dividing the speech signal into speech frames; transforming the speech frames from time domain to frequency domain; and extracting respective prosodic features for different frequency ranges. According to the above technical solution of the present invention, it is possible to effectively extract the prosodic feature which can combine with a traditional acoustics feature without any obstacle.

Method and apparatus for extracting prosodic feature of speech signal

A method and system for carrying out reliability classification for motion vectors in a video is proposed in the application. The method comprises: partitioning and searching step for partitioning a specified video frame of an input video, and searching motion vectors for a specified block of the specified video frame so as to generate a block matching error for the specified block; texture feature extracting step for extracting a texture feature of the specified block; and classifying-by-block step for carrying out reliability classification for the motion vectors for the specified block in accordance with the block matching error and the texture feature of the specified block.

Method and system for carrying out reliability classification for motion vectors in a video

The present invention provides a method for detecting a specific object in an image to be detected, including: a feature extraction step for extracting an image feature of the image to be detected; and a detection step for detecting detection windows with various sizes of the image to be detected according to the extracted image feature by using classifiers with various sizes corresponding to at least a part of the detection windows with various sizes, so as to determine the presence and location of a specific object in the image to be detected. The invention further provides an object detection device and a system including the device. The method, device and system for detecting a specific object in an image to be detected can improve the precision and increase the speed of the object detection.

Method and device of detecting object in image and system including the device

A motion capture apparatus includes: generating means; predicting means; projecting means; evaluating means; and estimating means. The generating means generates a kinematics model having joints connected to one another. The predicting means hierarchically calculates predicted positions at a current time of the joints of the objective person, and predicts three-dimensional positions and postures of the joints and the limbs. The projecting means projects the three-dimensional positions and postures of the joints and the limbs of the objective person on a two-dimensional image plane, the three-dimensional positions and the postures being predicted by predicting means. The evaluating means evaluates reliability about projection positions projected by the projecting means based on the observation image of the objective person. The estimating means estimates the three-dimensional positions and postures of the joints and the limbs of the objective person at the current time based on an evaluation result about the reliability.

Motion capture apparatus and method, and motion capture program

The present invention provides a foreground action estimating apparatus and a foreground action estimating method, wherein the foreground action estimating apparatus includes: a training image inputting means for inputting a foreground image, a background image and an image having the foreground and background images as training images; a basis matrix calculating means for calculating a foreground basis matrix and a background basis matrix by respectively extracting a foreground feature and a background feature from the foreground image and the background image, respectively, and combining the foreground basis matrix and the background basis matrix to obtain a combined basis matrix; a feature suppressing means for calculating the feature coefficients of the training images in accordance with the combined basis matrix obtained by the basis matrix calculating means so as to obtain image features of the background-feature-suppressed training images; and a foreground action information acquiring means for estimating foreground action information in accordance with a feature mapping matrix from the image feature to an action information set, by using the background-feature-suppressed image features.

Foreground action estimating apparatus and foreground action estimating method

The present invention provides a moving image analyzing apparatus, method and system. The moving image analyzing apparatus comprises a moving image reading means for reading a moving image, a region-of-interest extracting means for extracting a region-of-interest from each frame in the moving image, an object feature extracting means for extracting an object feature in the region-of-interest or a region adjacent to the region-of-interest, and a shot change detecting means for detecting a shot change on the basis of the color feature of image, the object feature of the region-of-interest, and the differences of the motion information among the images of each frame. By estimating the reliability of the motion information within an image, the present invention can eliminate the shot change which is incorrectly detected according to the color distribution feature and the dimensional feature of the region-of-interest, thereby improving the detection accuracy of shot change.

Video shot change detection based on color features, object features, and reliable motion information

The present invention discloses a system and method for segmenting foreground and background in a video, wherein the system comprises: a video shooting module for shooting the video; a data reading module for reading each frame of the video; a primary segmentation module for establishing a plurality of Gaussian models in a first color space for each pixel of each frame, and performing a matching processing between each pixel of the current frame and the plurality of Gaussian models corresponding to the pixel, and primarily segmenting the pixels as foreground and background according to the result of the matching processing; and a segmentation rejudging module for performing a rejudging processing to the primarily segmented foreground and background in a second color space, so as to obtain the finally determined foreground and background. The present invention improves the effect of foreground segmentation by using the combination of the color spaces and introducing the relationship between pixels.

System and method for segmenting foreground and background in a video

Disclosed herein is an object recognition device for recognition of an object that exists in an image, the device including: an edge image creator configured to create an edge image from a target image; a local feature extractor configured to extract a feature of each edge point on an edge image, and determine a base point and a support point from edge points in a local area defined for the edge image; a feature matching unit configured to implement, with reference to a memory, feature matching of a base point and a support point to thereby acquire a matching pair; and a matching pair determiner configured to determine final matching pairs by employing matching pairs having a highest matching cost among matching pairs obtained by the feature matching unit, wherein an object in a target image is identified based on matching pairs determined by the matching pair determiner.

Object recognition device, object recognition method, object recognition program, feature registration device, feature registration method, and feature registration program

Growing community of inventors

Beijing, China

Weiguo Wu