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1. 发明授权

US08406303B2 Motion estimation using prediction guided decimated search 有权
标题翻译：运动估计使用预测指导抽取搜索
公开(公告)号：US08406303B2
公开(公告)日：2013-03-26
申请号：US11638838
申请日：2006-12-14
申请人： Marc Hoffman , Wei Zhang , Raka Singh , Ke Ning
发明人： Marc Hoffman , Wei Zhang , Raka Singh , Ke Ning
IPC分类号： H04N11/04
CPC分类号： H04N19/57 , G06T7/223 , H04N19/523 , H04N19/533 , H04N19/557 , H04N19/56
摘要： A method and apparatus utilizing a prediction guided decimated search motion estimation algorithm are provided. The prediction guided decimated search motion estimation algorithm generates a motion vector used to encode a macroblock in a frame from a video sequence. The algorithm includes generating full-pixel seed vectors, performing a full-pixel search around the generated seed vectors, which is followed by a fractional pixel search. The full-pixel seed vectors generated are a predicted motion vector and a hierarchical motion vector. A fractional pixel search may be conducted around a final motion vector generated by the full-pixel search and may include a half-pixel search and a quarter-pixel search. The prediction guided decimated search motion estimation algorithm can be implemented in both software and hardware. The algorithm is characterized by improved efficiency, scalability, and decreased complexity.
摘要翻译：提供了利用预测引导抽取搜索运动估计算法的方法和装置。预测引导抽取搜索运动估计算法生成用于对来自视频序列的帧中的宏块进行编码的运动矢量。该算法包括生成全像素种子矢量，围绕生成的种子矢量执行全像素搜索，其后跟分数像素搜索。生成的全像素种子矢量是预测运动矢量和分层运动矢量。可以围绕由全像素搜索生成的最终运动矢量进行分数像素搜索，并且可以包括半像素搜索和四分之一像素搜索。预测引导的抽取搜索运动估计算法可以在软件和硬件两个方面实现。该算法的特征在于提高效率，可扩展性和降低的复杂性。

2. 发明申请

US20070183504A1 Motion estimation using prediction guided decimated search 有权
标题翻译：运动估计使用预测指导抽取搜索
公开(公告)号：US20070183504A1
公开(公告)日：2007-08-09
申请号：US11638838
申请日：2006-12-14
申请人： Marc Hoffman , Wei Zhang , Raka Singh , Ke Ning
发明人： Marc Hoffman , Wei Zhang , Raka Singh , Ke Ning
IPC分类号： H04N11/02 , H04N7/12
CPC分类号： H04N19/57 , G06T7/223 , H04N19/523 , H04N19/533 , H04N19/557 , H04N19/56
摘要： A method and apparatus utilizing a prediction guided decimated search motion estimation algorithm are provided. The prediction guided decimated search motion estimation algorithm generates a motion vector used to encode a macroblock in a frame from a video sequence. The algorithm includes generating full-pixel seed vectors, performing a full-pixel search around the generated seed vectors, which is followed by a fractional pixel search. The full-pixel seed vectors generated are a predicted motion vector and a hierarchical motion vector. A fractional pixel search may be conducted around a final motion vector generated by the full-pixel search and may include a half-pixel search and a quarter-pixel search. The prediction guided decimated search motion estimation algorithm can be implemented in both software and hardware. The algorithm is characterized by improved efficiency, scalability, and decreased complexity.
摘要翻译：提供了利用预测引导抽取搜索运动估计算法的方法和装置。预测引导抽取搜索运动估计算法生成用于对来自视频序列的帧中的宏块进行编码的运动矢量。该算法包括生成全像素种子矢量，围绕生成的种子矢量执行全像素搜索，其后跟分数像素搜索。生成的全像素种子矢量是预测运动矢量和分层运动矢量。可以围绕由全像素搜索生成的最终运动矢量进行分数像素搜索，并且可以包括半像素搜索和四分之一像素搜索。预测引导的抽取搜索运动估计算法可以在软件和硬件两个方面实现。该算法的特征在于提高效率，可扩展性和降低的复杂性。

3. 发明授权

US08699813B2 Adaptive filter for low-light noise reduction 有权
标题翻译：自适应滤波器，用于低光降噪
公开(公告)号：US08699813B2
公开(公告)日：2014-04-15
申请号：US12950666
申请日：2010-11-19
申请人： Raka Singh , Gaurav Malik , Rajesh Mahapatra
发明人： Raka Singh , Gaurav Malik , Rajesh Mahapatra
IPC分类号： G06K9/40
CPC分类号： H04N5/213
摘要： In general, in one embodiment, low-light noise is removed from an image by separately filtering luma and chroma components of the image, by adaptively filtering the image based at least in part on a Gaussian distribution of the image, and/or by dividing the image into separate regions and filtering each region separately.
摘要翻译：通常，在一个实施例中，通过分别过滤图像的亮度和色度分量，通过至少部分地基于图像的高斯分布和/或分割来自适应地过滤图像，从而从图像中去除低光噪声将图像分成不同的区域并分别过滤每个区域。

4. 发明申请

US20220108199A1 PIPELINING AND PARALLELISM FOR IMPLEMENTING A MIXTURE MODEL 有权
公开(公告)号：US20220108199A1
公开(公告)日：2022-04-07
申请号：US17521705
申请日：2021-11-08
申请人： Raka Singh
发明人： Raka Singh
IPC分类号： G06N7/00
摘要： One factor in limiting the speed of conventional implementations of mixture models is that the algorithm involves many decisions where different operations are fetched and performed depending on the outcome of the decisions. These decisions cause flushing of the pipeline, and thus prevent the realization of a highly parallel pipeline in a processor. Without parallelism, the throughput of the pipeline in the processor, i.e., the ability to process many samples of the digital input at a time, is limited. To alleviate this issue, implementation of the mixture model is reformulated, among other things, by embedding decisions into the process flow as multiplicative factors. The resulting implementation alleviates the need to use if-else statements for the decisions and reduces the number of times the pipeline has to be flushed. The implementation enables a pipeline with a higher degree of parallelism and thereby increases throughput and speed of the implementation.

5. 发明授权

US08755625B2 Component filtering for low-light noise reduction 有权
标题翻译：用于低光噪声降低的元件滤波
公开(公告)号：US08755625B2
公开(公告)日：2014-06-17
申请号：US12950664
申请日：2010-11-19
申请人： Raka Singh , Gaurav Malik , Rajesh Mahapatra
发明人： Raka Singh , Gaurav Malik , Rajesh Mahapatra
IPC分类号： G06K9/40
CPC分类号： G06T5/002 , G06K9/40 , G06T5/30 , G06T2207/20032 , G06T2207/20192 , H04N1/409 , H04N1/58 , H04N9/646
摘要： In general, in one embodiment, low-light noise is removed from an image by separately filtering luma and chroma components of the image, by adaptively filtering the image based at least in part on a Gaussian distribution of the image, and/or by dividing the image into separate regions and filtering each region separately.
摘要翻译：通常，在一个实施例中，通过分别过滤图像的亮度和色度分量，通过至少部分地基于图像的高斯分布和/或分割来自适应地过滤图像，从而从图像中去除低光噪声将图像分成不同的区域并分别过滤每个区域。

6. 发明申请

US20170011261A1 VIDEO PROCESSING FOR HUMAN OCCUPANCY DETECTION 审中-公开
标题翻译：视频处理人体检测
公开(公告)号：US20170011261A1
公开(公告)日：2017-01-12
申请号：US14794991
申请日：2015-07-09
申请人： Raka Singh
发明人： Raka Singh
IPC分类号： G06K9/00 , G06T7/20
CPC分类号： G06K9/00369 , G06K9/00771 , G06K9/00832 , G06T2207/10016 , G06T2207/30196
摘要： Many conventional video processing algorithms attempting to detect human presence in a video stream often generate false positives on non-human movements such as plants moving in the wind, rotating fan, etc. To reduce false positives, a technique exploiting temporal correlation of non-human movements can accurately detect human occupancy while reject non-human movements. Specifically, the technique involves performing temporal analysis on a time-series signal generated based on an accumulation of foreground maps and an accumulation of motion map and analyzing the running mean and the running variance of the time-series signal. By determining whether the time-series signal is correlated in time, the technique is able to distinguish human movements and non-human movements. Besides having superior accuracy, the technique lends itself to an efficient algorithm which can be implemented on low cost, low power digital signal processor or other suitable hardware.
摘要翻译：试图在视频流中检测人类存在的许多传统视频处理算法通常在诸如在风中运动的植物，旋转风扇等非人类运动上产生假阳性。为了减少误报，一种利用非人类时间相关性的技术运动可以准确地检测人的占用，同时拒绝非人类的运动。具体地说，该技术涉及对基于前景地图的积累和运动图的积累而生成的时间序列信号进行时间分析，并分析时间序列信号的运行平均值和运行方差。通过确定时间序列信号是否与时间相关，该技术能够区分人类运动和非人类运动。除了具有更高的精度外，该技术还适用于可在低成本，低功耗数字信号处理器或其他合适的硬件上实现的高效算法。

7. 发明申请

US20120128243A1 COMPONENT FILTERING FOR LOW-LIGHT NOISE REDUCTION 有权
标题翻译：用于低照度噪声减少的组件滤波器
公开(公告)号：US20120128243A1
公开(公告)日：2012-05-24
申请号：US12950664
申请日：2010-11-19
申请人： Raka Singh , Gaurav Malik , Rajesh Mahapatra
发明人： Raka Singh , Gaurav Malik , Rajesh Mahapatra
IPC分类号： G06K9/40
CPC分类号： G06T5/002 , G06K9/40 , G06T5/30 , G06T2207/20032 , G06T2207/20192 , H04N1/409 , H04N1/58 , H04N9/646
摘要： In general, in one embodiment, low-light noise is removed from an image by separately filtering luma and chroma components of the image, by adaptively filtering the image based at least in part on a Gaussian distribution of the image, and/or by dividing the image into separate regions and filtering each region separately.
摘要翻译：通常，在一个实施例中，通过分别过滤图像的亮度和色度分量，通过至少部分地基于图像的高斯分布和/或分割来自适应地过滤图像，从而从图像中去除低光噪声将图像分成不同的区域并分别过滤每个区域。

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