会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 2. 发明申请
    • METHOD FOR COMPUTING FOOD VOLUME IN A METHOD FOR ANALYZING FOOD
    • 用于分析食物的方法中的食物体积的方法
    • US20110182477A1
    • 2011-07-28
    • US12758208
    • 2010-04-12
    • Amir TamrakarHarpreet Singh SawhneyQian YuAjay Divakaran
    • Amir TamrakarHarpreet Singh SawhneyQian YuAjay Divakaran
    • G06K9/00
    • G06T7/0002G06T7/44G06T7/593G06T7/62G06T7/77G06T2207/20016G06T2207/30128
    • A computer-implemented method for estimating a volume of at least one food item on a food plate is disclosed. A first and second plurality of images are received from different positions above a food plate, wherein angular spacing between the positions of the first plurality of images is greater than angular spacing between the positions of the second plurality of images. A first set of poses of each of the first plurality of images is estimated. A second set of poses of each of the second plurality of images is estimated based on at least the first set of poses. A pair of images taken from each of the first and second plurality of images is rectified based on at least the first and second set of poses. A 3D point cloud is reconstructed based on at least the rectified pair of images. At least one surface of the at least one food item above the food plate is estimated based on at least the reconstructed 3D point cloud. The volume of the at least one food item is estimated based on the at least one surface.
    • 公开了一种用于估计食品板上的至少一种食品的体积的计算机实现的方法。 从食品牌上方的不同位置接收第一和第二多个图像,其中第一多个图像的位置之间的角度间隔大于第二多个图像的位置之间的角度间隔。 估计第一多个图像中的每一个的第一组姿势。 基于至少第一组姿势来估计第二组多个图像中的每一个的第二组姿势。 从第一和第二多个图像中的每一个拍摄的一对图像至少基于第一和第二组姿势进行整改。 至少基于整流图像对来重构3D点云。 基于至少重构的3D点云来估计食物板上方的至少一个食物的至少一个表面。 基于至少一个表面来估计至少一个食物的体积。
    • 10. 发明授权
    • Method for segmenting 3D objects from compressed videos
    • 从压缩视频分割3D对象的方法
    • US07142602B2
    • 2006-11-28
    • US10442417
    • 2003-05-21
    • Fatih M. PorikliHuifang SunAjay Divakaran
    • Fatih M. PorikliHuifang SunAjay Divakaran
    • H04B1/66
    • G06K9/34G06T7/11G06T7/187G06T2207/10016G06T2207/20048G06T2207/20101H04N19/48H04N19/87
    • A method segments a video into objects, without user assistance. An MPEG compressed video is converted to a structure called a pseudo spatial/temporal data using DCT coefficients and motion vectors. The compressed video is first parsed and the pseudo spatial/temporal data are formed. Seeds macro-blocks are identified using, e.g., the DCT coefficients and changes in the motion vector of macro-blocks.A video volume is “grown” around each seed macro-block using the DCT coefficients and motion distance criteria. Self-descriptors are assigned to the volume, and mutual descriptors are assigned to pairs of similar volumes. These descriptors capture motion and spatial information of the volumes. Similarity scores are determined for each possible pair-wise combination of volumes. The pair of volumes that gives the largest score is combined iteratively. In the combining stage, volumes are classified and represented in a multi-resolution coarse-to-fine hierarchy of video objects.
    • 一种方法是将视频分割成对象,而无需用户帮助。 使用DCT系数和运动矢量将MPEG压缩视频转换成称为伪空间/时间数据的结构。 首先解压缩视频并形成伪空间/时间数据。 使用例如DCT系数和宏块的运动矢量的变化来识别种子宏块。 使用DCT系数和运动距离标准,在每个种子宏块周围“生长”视频量。 自描述符被分配给卷,并且相互描述符被分配给相似卷的对。 这些描述符捕获卷的运动和空间信息。 确定每个可能的成对组合的相似度分数。 给出最大分数的一对卷被迭代地组合。 在组合阶段,卷被分类并以视频对象的多分辨率粗到精细层级来表示。