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    • 4. 发明授权
    • Apparatus, method and computer-readable medium generating depth map
    • 仪器,方法和计算机可读介质生成深度图
    • US08553972B2
    • 2013-10-08
    • US12830822
    • 2010-07-06
    • Ji Won KimGangyu MaHaitao WangXiying WangJi Yeun KimYong Ju Jung
    • Ji Won KimGangyu MaHaitao WangXiying WangJi Yeun KimYong Ju Jung
    • G06K9/00G06K9/32H04N13/00
    • G06T7/50G06T2207/10016G06T2207/20221G06T2207/30196
    • Disclosed are an apparatus, a method and a computer-readable medium automatically generating a depth map corresponding to each two-dimensional (2D) image in a video. The apparatus includes an image acquiring unit to acquire a plurality of 2D images that are temporally consecutive in an input video, a saliency map generator to generate at least one saliency map corresponding to a current 2D image among the plurality of 2D images based on a Human Visual Perception (HVP) model, a saliency-based depth map generator, a three-dimensional (3D) structure matching unit to calculate matching scores between the current 2D image and a plurality of 3D typical structures that are stored in advance, and to determine a 3D typical structure having a highest matching score among the plurality of 3D typical structures to be a 3D structure of the current 2D image, a matching-based depth map generator; a combined depth map generator to combine the saliency-based depth map and the matching-based depth map and to generate a combined depth map, and a spatial and temporal smoothing unit to spatially and temporally smooth the combined depth map.
    • 公开了一种自动生成与视频中的每个二维(2D)图像相对应的深度图的装置,方法和计算机可读介质。 该装置包括:图像获取单元,用于获取在输入视频中在时间上连续的多个2D图像,显着图生成器,用于基于人类生成与多个2D图像中的当前2D图像相对应的至少一个显着图 视觉感知(HVP)模型,基于显着性的深度图生成器,三维(3D)结构匹配单元,用于计算当前2D图像与预先存储的多个3D典型结构之间的匹配分数,并且确定 在所述多个3D典型结构中具有最高匹配分数以作为当前2D图像的3D结构的3D典型结构,基于匹配的深度图生成器; 组合深度图生成器,用于组合基于显着性的深度图和基于匹配的深度图并生成组合深度图,以及空间和时间平滑单元,以空间和时间平滑组合的深度图。
    • 5. 发明申请
    • APPARATUS, METHOD AND COMPUTER-READABLE MEDIUM GENERATING DEPTH MAP
    • 装置,方法和计算机可读介质生成深度图
    • US20110026808A1
    • 2011-02-03
    • US12830822
    • 2010-07-06
    • Ji Won KIMGangyu MaHaitao WangXiying WangJi Yeun KimYong Ju Jung
    • Ji Won KIMGangyu MaHaitao WangXiying WangJi Yeun KimYong Ju Jung
    • G06T7/00
    • G06T7/50G06T2207/10016G06T2207/20221G06T2207/30196
    • Disclosed are an apparatus, a method and a computer-readable medium automatically generating a depth map corresponding to each two-dimensional (2D) image in a video. The apparatus includes an image acquiring unit to acquire a plurality of 2D images that are temporally consecutive in an input video, a saliency map generator to generate at least one saliency map corresponding to a current 2D image among the plurality of 2D images based on a Human Visual Perception (HVP) model, a saliency-based depth map generator, a three-dimensional (3D) structure matching unit to calculate matching scores between the current 2D image and a plurality of 3D typical structures that are stored in advance, and to determine a 3D typical structure having a highest matching score among the plurality of 3D typical structures to be a 3D structure of the current 2D image, a matching-based depth map generator; a combined depth map generator to combine the saliency-based depth map and the matching-based depth map and to generate a combined depth map, and a spatial and temporal smoothing unit to spatially and temporally smooth the combined depth map.
    • 公开了一种自动生成与视频中的每个二维(2D)图像相对应的深度图的装置,方法和计算机可读介质。 该装置包括:图像获取单元,用于获取在输入视频中在时间上连续的多个2D图像,显着图生成器,用于基于人类生成与多个2D图像中的当前2D图像相对应的至少一个显着图 视觉感知(HVP)模型,基于显着性的深度图生成器,三维(3D)结构匹配单元,用于计算当前2D图像与预先存储的多个3D典型结构之间的匹配分数,并且确定 在所述多个3D典型结构中具有最高匹配分数以作为当前2D图像的3D结构的3D典型结构,基于匹配的深度图生成器; 组合深度图生成器,用于组合基于显着性的深度图和基于匹配的深度图并生成组合深度图,以及空间和时间平滑单元,以空间和时间平滑组合的深度图。
    • 9. 发明申请
    • Method, system, and medium for classifying category of photo
    • 方法,系统和介质,用于分类照片类别
    • US20080013940A1
    • 2008-01-17
    • US11605281
    • 2006-11-29
    • Yong Ju JungSang Kyun KimJi Yeun Kim
    • Yong Ju JungSang Kyun KimJi Yeun Kim
    • G03B17/00
    • G03D15/001
    • A photo category classification method including dividing a region of a photo based on content of the photo and extracting a visual feature from the segmented region of the photo, modeling at least one local semantic concept included in the photo according to the extracted visual feature, acquiring a posterior probability value from confidence values acquired from the modeling of the at least one local semantic concept by normalization using regression analysis, modeling a global semantic concept included in the photo by using the posterior probability value of the at least one local semantic concept; and removing classification noise from a confidence value acquired from the modeling the global semantic concept.
    • 一种照片类别分类方法,包括基于照片的内容划分照片的区域并从照片的分割区域提取视觉特征,根据所提取的视觉特征对包括在照片中的至少一个局部语义概念进行建模,获取 通过使用回归分析的归一化从所述至少一个局部语义概念的建模获得的置信度值的后验概率值,通过使用所述至少一个局部语义概念的后验概率值来对包含在所述照片中的全局语义概念进行建模; 以及从对全局语义概念的建模获得的置信度值中去除分类噪声。