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1. 发明申请

US20100208941A1 ACTIVE COORDINATED TRACKING FOR MULTI-CAMERA SYSTEMS 有权
标题翻译：主动协调跟踪多摄像机系统
公开(公告)号：US20100208941A1
公开(公告)日：2010-08-19
申请号：US12704189
申请日：2010-02-11
申请人： Christopher P. Broaddus , Thomas Germano , Nicholas Vandervalk , Shunguang Wu , Ajay Divakaran , Harpreet Singh Sawhney
发明人： Christopher P. Broaddus , Thomas Germano , Nicholas Vandervalk , Shunguang Wu , Ajay Divakaran , Harpreet Singh Sawhney
IPC分类号： G06T7/00
CPC分类号： G01S13/867 , G01S3/7864 , G01S13/726 , G06T7/194 , G06T7/292 , G06T2207/20076 , G06T2207/30232 , G08B13/19608 , G08B13/19645 , G08B13/19697
摘要： A method and system for coordinated tracking of objects is disclosed. A plurality of images is received from a plurality of nodes, each node comprising at least one image capturing device. At least one target in the plurality of images is identified to produce at least one local track corresponding to each of the plurality of nodes having the at least one target in its field of view. The at least one local track corresponding to each of the plurality of nodes is fused according to a multi-hypothesis tracking method to produce at least one fused track corresponding to the at least one target. At least one of the plurality of nodes is assigned to track the at least one target based on minimizing at least one cost function comprising a cost matrix using the k-best algorithm for tracking at least one target for each of the plurality of nodes. The at least one fused track is sent to the at least one of the plurality of nodes assigned to track the at least one target based on the at least one fused track.
摘要翻译：公开了一种协调跟踪物体的方法和系统。从多个节点接收多个图像，每个节点包括至少一个图像捕获装置。多个图像中的至少一个目标被识别以产生与其视场中具有至少一个目标的多个节点中的每一个对应的至少一个本地轨迹。根据多假设跟踪方法将与多个节点中的每一个相对应的至少一个本地轨道融合以产生至少一个对应于该至少一个目标的融合轨道。所述多个节点中的至少一个被分配以跟踪所述至少一个目标，所述至少一个目标基于最小化至少一个成本函数，所述至少一个成本函数包括使用所述k-最佳算法的成本矩阵，用于跟踪所述多个节点中的每个节点的至少一个目至少一个融合轨道被发送到被分配以基于至少一个融合轨道跟踪至少一个目标的多个节点中的至少一个。

2. 发明授权

US08180107B2 Active coordinated tracking for multi-camera systems 有权
标题翻译：主动协调跟踪多摄像机系统
公开(公告)号：US08180107B2
公开(公告)日：2012-05-15
申请号：US12704189
申请日：2010-02-11
申请人： Christopher P. Broaddus , Thomas Germano , Nicholas Vandervalk , Shunguang Wu , Ajay Divakaran , Harpreet Singh Sawhney
发明人： Christopher P. Broaddus , Thomas Germano , Nicholas Vandervalk , Shunguang Wu , Ajay Divakaran , Harpreet Singh Sawhney
IPC分类号： G06K9/00 , H04N7/18
CPC分类号： G01S13/867 , G01S3/7864 , G01S13/726 , G06T7/194 , G06T7/292 , G06T2207/20076 , G06T2207/30232 , G08B13/19608 , G08B13/19645 , G08B13/19697
摘要： A method and system for coordinated tracking of objects is disclosed. A plurality of images is received from a plurality of nodes, each node comprising at least one image capturing device. At least one target in the plurality of images is identified to produce at least one local track corresponding to each of the plurality of nodes having the at least one target in its field of view. The at least one local track corresponding to each of the plurality of nodes is fused according to a multi-hypothesis tracking method to produce at least one fused track corresponding to the at least one target. At least one of the plurality of nodes is assigned to track the at least one target based on minimizing at least one cost function comprising a cost matrix using the k-best algorithm for tracking at least one target for each of the plurality of nodes. The at least one fused track is sent to the at least one of the plurality of nodes assigned to track the at least one target based on the at least one fused track.
摘要翻译：公开了一种协调跟踪物体的方法和系统。从多个节点接收多个图像，每个节点包括至少一个图像捕获装置。多个图像中的至少一个目标被识别以产生与其视场中具有至少一个目标的多个节点中的每一个对应的至少一个本地轨迹。根据多假设跟踪方法将与多个节点中的每一个相对应的至少一个本地轨道融合以产生至少一个对应于该至少一个目标的融合轨道。所述多个节点中的至少一个被分配以跟踪所述至少一个目标，所述至少一个目标基于最小化至少一个成本函数，所述至少一个成本函数包括使用所述k最佳算法的成本矩阵，用于跟踪所述多个节点中的每个节点的至少一个目标。至少一个融合轨道被发送到被分配以基于至少一个融合轨道跟踪至少一个目标的多个节点中的至少一个。

3. 发明授权

US08385154B2 Weapon identification using acoustic signatures across varying capture conditions 有权
标题翻译：使用声学签名的武器识别在不同的捕获条件下
公开(公告)号：US08385154B2
公开(公告)日：2013-02-26
申请号：US12766219
申请日：2010-04-23
申请人： Saad Khan , Ajay Divakaran , Harpreet Singh Sawhney
发明人： Saad Khan , Ajay Divakaran , Harpreet Singh Sawhney
IPC分类号： G01S3/80
CPC分类号： G10L25/48
摘要： A computer implemented method for automatically detecting and classifying acoustic signatures across a set of recording conditions is disclosed. A first acoustic signature is received. The first acoustic signature is projected into a space of a minimal set of exemplars of acoustic signature types derived from a larger set of exemplars using a wrapper method. At least one vector distance is calculated between the projected acoustic signature and each exemplar of the minimal set of exemplars. An exemplar is selected from the minimal set of exemplars having the smallest vector distance to the projected acoustic signature as a class corresponding to and classifying the first acoustic signature. The first acoustic signature and the plurality of acoustic signatures may correspond to one of gunshots, musical instruments, songs, and speech. The minimal set of exemplars may correspond to a hierarchy of acoustic signature types.
摘要翻译：公开了一种用于在一组记录条件下自动检测和分类声学签名的计算机实现的方法。接收到第一个声学签名。第一声学签名被投影到使用包装方法从更大的样本集合导出的声学签名类型的最小样本集合的空间中。在投影的声学特征与最小样本集的每个样本之间计算至少一个矢量距离。从具有与投影的声学签名的最小向量距离的最小样本集合中选择一个范例作为对应于和分类第一声学签名的类别。第一声学签名和多个声学签名可以对应于枪声，乐器，歌曲和语音之一。最小的一组样本可以对应于声学签名类型的层级。

4. 发明申请

US20120106800A1 3-D MODEL BASED METHOD FOR DETECTING AND CLASSIFYING VEHICLES IN AERIAL IMAGERY 有权
标题翻译：用于在航空影像中检测和分类车辆的基于3-D模型的方法
公开(公告)号：US20120106800A1
公开(公告)日：2012-05-03
申请号：US12913861
申请日：2010-10-28
申请人： Saad Masood Khan , Hui Cheng , Dennis Lee Matthies , Harpreet Singh Sawhney , Sang-Hack Jung , Chris Broaddus , Bogdan Calin Mihai Matei , Ajay Divakaran
发明人： Saad Masood Khan , Hui Cheng , Dennis Lee Matthies , Harpreet Singh Sawhney , Sang-Hack Jung , Chris Broaddus , Bogdan Calin Mihai Matei , Ajay Divakaran
IPC分类号： G06K9/68
CPC分类号： G06K9/00785 , B64C39/024 , B64C2201/123 , B64D47/08 , G06K9/00651 , G06K9/4671 , G06K9/6269 , G06K9/6282 , G06T7/11 , G06T7/20 , G06T2207/10012
摘要： A computer implemented method for determining a vehicle type of a vehicle detected in an image is disclosed. An image having a detected vehicle is received. A number of vehicle models having salient feature points is projected on the detected vehicle. A first set of features derived from each of the salient feature locations of the vehicle models is compared to a second set of features derived from corresponding salient feature locations of the detected vehicle to form a set of positive match scores (p-scores) and a set of negative match scores (n-scores). The detected vehicle is classified as one of the vehicle models models based at least in part on the set of p-scores and the set of n-scores.
摘要翻译：公开了一种用于确定在图像中检测到的车辆的车辆类型的计算机实现的方法。接收具有检测到的车辆的图像。在检测到的车辆上投影出具有显着特征点的多个车辆模型。将来自车辆模型的每个突出特征位置的第一组特征与从所检测到的车辆的相应突出特征位置导出的第二组特征进行比较，以形成一组正的匹配得分（p分数）和一组负面比赛得分（n分）。检测到的车辆至少部分地基于p分数集合和n分数集合被分类为车辆模型模型之一。

5. 发明授权

US08913783B2 3-D model based method for detecting and classifying vehicles in aerial imagery 有权
标题翻译：基于3-D模型的航空图像检测和分类车辆的方法
公开(公告)号：US08913783B2
公开(公告)日：2014-12-16
申请号：US12913861
申请日：2010-10-28
申请人： Saad Masood Khan , Hui Cheng , Dennis Lee Matthies , Harpreet Singh Sawhney , Sang-Hack Jung , Chris Broaddus , Bogdan Calin Mihai Matei , Ajay Divakaran
发明人： Saad Masood Khan , Hui Cheng , Dennis Lee Matthies , Harpreet Singh Sawhney , Sang-Hack Jung , Chris Broaddus , Bogdan Calin Mihai Matei , Ajay Divakaran
IPC分类号： G06K9/00 , G06K9/46
CPC分类号： G06K9/00785 , B64C39/024 , B64C2201/123 , B64D47/08 , G06K9/00651 , G06K9/4671 , G06K9/6269 , G06K9/6282 , G06T7/11 , G06T7/20 , G06T2207/10012
摘要： A computer implemented method for determining a vehicle type of a vehicle detected in an image is disclosed. An image having a detected vehicle is received. A number of vehicle models having salient feature points is projected on the detected vehicle. A first set of features derived from each of the salient feature locations of the vehicle models is compared to a second set of features derived from corresponding salient feature locations of the detected vehicle to form a set of positive match scores (p-scores) and a set of negative match scores (n-scores). The detected vehicle is classified as one of the vehicle models models based at least in part on the set of p-scores and the set of n-scores.
摘要翻译：公开了一种用于确定在图像中检测到的车辆的车辆类型的计算机实现的方法。接收具有检测到的车辆的图像。在检测到的车辆上投影出具有显着特征点的多个车辆模型。将来自车辆模型的每个突出特征位置的第一组特征与从所检测到的车辆的相应突出特征位置导出的第二组特征进行比较，以形成一组正的匹配得分（p分数）和一组负面比赛得分（n分）。检测到的车辆至少部分地基于p分数集合和n分数集合被分类为车辆模型模型之一。

6. 发明授权

US08345930B2 Method for computing food volume in a method for analyzing food 有权
标题翻译：食物分析方法计算食物量的方法
公开(公告)号：US08345930B2
公开(公告)日：2013-01-01
申请号：US12758208
申请日：2010-04-12
申请人： Amir Tamrakar , Harpreet Singh Sawhney , Qian Yu , Ajay Divakaran
发明人： Amir Tamrakar , Harpreet Singh Sawhney , Qian Yu , Ajay Divakaran
IPC分类号： G06K9/00
CPC分类号： G06T7/0002 , G06T7/44 , G06T7/593 , G06T7/62 , G06T7/77 , G06T2207/20016 , G06T2207/30128
摘要： 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.
摘要翻译：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。

7. 发明授权

US08330819B2 Method for pose invariant vessel fingerprinting 有权
标题翻译：姿态不变血管指纹方法
公开(公告)号：US08330819B2
公开(公告)日：2012-12-11
申请号：US12758507
申请日：2010-04-12
申请人： Sang-Hack Jung , Ajay Divakaran , Harpreet Singh Sawhney
发明人： Sang-Hack Jung , Ajay Divakaran , Harpreet Singh Sawhney
IPC分类号： H04N7/18
CPC分类号： G06K9/00771 , G06K9/6206 , G06K9/6211
摘要： A computer-implemented method for for matching objects is disclosed. At least two images where one of the at least two images has a first target object and a second of the at least two images has a second target object are received. At least one first patch from the first target object and at least one second patch from the second target object are extracted. A distance-based part encoding between each of the at least one first patch and the at least one second patch based upon a corresponding codebook of image parts including at least one of part type and pose is constructed. A viewpoint of one of the at least one first patch is warped to a viewpoint of the at least one second patch. A parts level similarity measure based on the view-invariant distance measure for each of the at least one first patch and the at least one second patch is applied to determine whether the first target object and the second target object are the same or different objects.
摘要翻译：公开了一种用于匹配对象的计算机实现的方法。接收至少两个图像，其中至少两个图像中的一个具有第一目标对象，并且至少两个图像中的第二图像具有第二目标对象。提取来自第一目标对象的至少一个第一补丁和来自第二目标对象的至少一个第二补丁。构建基于包括部件类型和姿态中的至少一个的图像部件的对应码本的至少一个第一贴片和至少一个第二贴片中的每一个之间的基于距离的部件编码。所述至少一个第一贴片中的一个的视点弯曲到所述至少一个第二贴片的观点。应用基于对于至少一个第一贴片和至少一个第二贴片中的每一个的视图不变距离度量的零件级相似性度量来确定第一目标对象和第二目标对象是相同还是不同的对象。

8. 发明申请

US20100271905A1 WEAPON IDENTIFICATION USING ACOUSTIC SIGNATURES ACROSS VARYING CAPTURE CONDITIONS 有权
标题翻译：使用声音识别的武器识别符合各种不同的捕获条件
公开(公告)号：US20100271905A1
公开(公告)日：2010-10-28
申请号：US12766219
申请日：2010-04-23
申请人： Saad Khan , Ajay Divakaran , Harpreet Singh Sawhney
发明人： Saad Khan , Ajay Divakaran , Harpreet Singh Sawhney
IPC分类号： G01S3/80
CPC分类号： G10L25/48
摘要： A computer implemented method for automatically detecting and classifying acoustic signatures across a set of recording conditions is disclosed. A first acoustic signature is received. The first acoustic signature is projected into a space of a minimal set of exemplars of acoustic signature types derived from a larger set of exemplars using a wrapper method. At least one vector distance is calculated between the projected acoustic signature and each exemplar of the minimal set of exemplars. An exemplar is selected from the minimal set of exemplars having the smallest vector distance to the projected acoustic signature as a class corresponding to and classifying the first acoustic signature. The first acoustic signature and the plurality of acoustic signatures may correspond to one of gunshots, musical instruments, songs, and speech. The minimal set of exemplars may correspond to a hierarchy of acoustic signature types.
摘要翻译：公开了一种用于在一组记录条件下自动检测和分类声学签名的计算机实现的方法。接收到第一个声学签名。第一声学签名被投影到使用包装方法从更大的样本集合导出的声学签名类型的最小样本集合的空间中。在投影的声学特征与最小样本集的每个样本之间计算至少一个矢量距离。从具有与投影的声学签名的最小向量距离的最小样本集合中选择一个示例作为对应于和分类第一声学签名的类别。第一声学签名和多个声学签名可以对应于枪声，乐器，歌曲和语音之一。最小的一组样本可以对应于声学签名类型的层级。

9. 发明授权

US09053194B2 Method and apparatus for correlating and viewing disparate data 有权
标题翻译：用于关联和查看不同数据的方法和装置
公开(公告)号：US09053194B2
公开(公告)日：2015-06-09
申请号：US13484520
申请日：2012-05-31
申请人： Harpreet Singh Sawhney , Jayakrishnan Eledath , Ajay Divakaran , Mayank Bansal , Hui Cheng
发明人： Harpreet Singh Sawhney , Jayakrishnan Eledath , Ajay Divakaran , Mayank Bansal , Hui Cheng
IPC分类号： G06F17/30
CPC分类号： G06F17/2785 , G06F17/30047 , G06F17/30867 , G06F17/3087
摘要： A computer-implemented method comprising collecting data from a plurality of information sources, identifying a geographic location associated with the data and forming a corresponding event according to the geographic location, correlating the data and the event with one or more topics based at least partly on the identified geographic location and storing the correlated data and event and inferring the associated geographic location if the data does not comprise explicit location information, including matching the data against a database of geo-referenced data.
摘要翻译：一种计算机实现的方法，包括从多个信息源收集数据，识别与所述数据相关联的地理位置并根据所述地理位置形成对应的事件，至少部分地基于所述数据和所述事件与一个或多个主题相关联所识别的地理位置并存储相关数据和事件，并且如果数据不包括显式位置信息，则推断相关联的地理位置，包括将数据与地理参考数据的数据库进行匹配。

10. 发明申请

US20110182477A1 METHOD FOR COMPUTING FOOD VOLUME IN A METHOD FOR ANALYZING FOOD 有权
标题翻译：用于分析食物的方法中的食物体积的方法
公开(公告)号：US20110182477A1
公开(公告)日：2011-07-28
申请号：US12758208
申请日：2010-04-12
申请人： Amir Tamrakar , Harpreet Singh Sawhney , Qian Yu , Ajay Divakaran
发明人： Amir Tamrakar , Harpreet Singh Sawhney , Qian Yu , Ajay Divakaran
IPC分类号： G06K9/00
CPC分类号： G06T7/0002 , G06T7/44 , G06T7/593 , G06T7/62 , G06T7/77 , G06T2207/20016 , G06T2207/30128
摘要： 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.
摘要翻译：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。

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