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公开(公告)号：WO2016095023A1
公开(公告)日：2016-06-23
申请号：PCT/CA2015/051261
申请日：2015-12-02
发明人： MISHRA, Akshaya K. , EICHEL, Justin A. , SWANSON, Douglas J. , JANKOVIC, Nicholas D. , MILLER, Nicholas
CPC分类号： H04N19/136 , G06K9/00718 , G06K9/00785 , H04N19/20 , H04N19/426
摘要： A system and method are provided for compressing video data, the method comprising: obtaining video data; extracting at least one object of interest from the video data using at least one classifier associated with at least one feature detectable in the video data; and preparing compressed video data comprising at least one object of interest extracted from the video data.
摘要翻译： 提供了一种用于压缩视频数据的系统和方法，所述方法包括：获得视频数据; 使用与所述视频数据中可检测的至少一个特征相关联的至少一个分类器从所述视频数据中提取至少一个关注对象; 以及制备包括从所述视频数据提取的至少一个感兴趣对象的压缩视频数据。
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公开(公告)号：WO2017035663A1
公开(公告)日：2017-03-09
申请号：PCT/CA2016/051045
申请日：2016-09-02
CPC分类号： G06K9/00785 , G06K9/00771 , G06K9/481 , G06K9/623 , G06K2009/3291 , G06T7/0024 , G06T7/0034 , G06T7/004 , G06T7/2033 , G06T7/2093 , G06T7/246 , G06T2207/10016 , G06T2207/20081 , G06T2207/30236 , G06T2207/30252
摘要： A system and method are provided for mapping spatial and temporal measurements of motion constrained objects in a scene, e.g., vehicles. The method comprises determining a location parameter, and/or other interesting properties, for each of a plurality of objects at a plurality of points over time; generating a vector field over location and time using the location parameters, to specify the motion of each object over time; deriving measurements for each object using velocities from the vector field for that object, as the object moves through the scene over time; and outputting both individual and aggregate object and object property flow for the plurality of objects. Combining the generated map with a network graph and/or network model can provide network flow insights useful for historic event analysis, network flow monitoring, and planning purposes.
摘要翻译： 提供了一种用于映射场景（例如车辆）中的运动约束对象的空间和时间测量的系统和方法。 该方法包括：在多个点上随时间确定多个对象中的每个对象的位置参数和/或其他感兴趣的属性; 使用位置参数在位置和时间上产生矢量场，以指定每个对象随时间的运动; 随着时间的推移，物体通过场景移动，从而为该物体的矢量场中的速度导出每个物体的测量结果; 并输出多个对象的个体和聚合对象和对象属性流。 将生成的图与网络图和/或网络模型结合可以提供对历史事件分析，网络流监视和规划目的有用的网络流洞见。
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3.发明申请
公开(公告)号：WO2015192239A1
公开(公告)日：2015-12-23
申请号：PCT/CA2015/050558
申请日：2015-06-18
发明人： MISHRA, Akshaya K. , MILLER, Nicholas , EICHEL, Justin A. , JANKOVIC, Nicholas , MCBRIDE, Kurtis N. , BRIJPAUL, Anthony I.
CPC分类号： G06K9/00785 , G06K9/00973 , G06K9/6254 , G06K9/6256 , G06N99/005
摘要： To address problems that video imaging systems and platforms face when analyzing image and video content for detection and feature extraction, a solution is provided in which accumulating significant amounts of data suitable for training and learning analytics is leveraged to improve over time, the classifiers used to perform the detection and feature extraction, by employing a larger search space and generate additional and more complex classifiers through distributed processing. A distributed learning platform is therefore provided, which is configured for operating on large scale data, in a true big data paradigm. The learning platform is operable to empirically estimate a set of optimal feature vectors and a set of discriminant functions using a parallelizable learning algorithm. A method of adding new data into a database utilized by such a learning platform is also provided. The method comprises identifying an unrepresented sample space; determining new data samples associated with the unrepresented sample space; and adding the new data samples to the database.
摘要翻译： 为了解决视频成像系统和平台在分析用于检测和特征提取的图像和视频内容时所面临的问题，提供了一种解决方案，其中积累了适合于训练和学习分析的大量数据以随着时间的推移而改进，分类器用于 通过采用更大的搜索空间并通过分布式处理生成额外的和更复杂的分类器来执行检测和特征提取。 因此，在真正的大数据范例中，提供了一种分布式学习平台，用于在大规模数据上进行操作。 学习平台可操作以使用可并行化学习算法经验性地估计一组最优特征向量和一组判别函数。 还提供了一种将新数据添加到由这种学习平台使用的数据库中的方法。 该方法包括识别未表示的样本空间; 确定与未表示的样本空间相关联的新数据样本; 并将新的数据样本添加到数据库。
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