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公开(公告)号：US20160148071A1
公开(公告)日：2016-05-26
申请号：US14551942
申请日：2014-11-24
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Kumar Arrakutti Desappan , Manu Mathew , Pramod Kumar Swami
CPC classification number: G06K9/4647 , G06K9/4652 , G06K9/6212
Abstract: An object detection system and a method of detecting an object in an image are disclosed. In an embodiment, a method for detecting the object includes computing one or more feature planes of one or more types for each image pixel of the image. A plurality of cells is defined in the image, where each cell includes first through nth number of pixels, and starting locations of each cell in the image in horizontal and vertical directions are integral multiples of predefined horizontal and vertical step sizes, respectively. One or more feature plane summations of one or more types are computed for each cell. A feature vector is determined for an image portion of the image based on a set of feature plane summations, and the feature vector is compared with a corresponding object classifier to detect a presence of the corresponding object in the image portion of the image.
Abstract translation: 公开了一种物体检测系统和检测图像中物体的方法。 在一个实施例中，用于检测对象的方法包括为图像的每个图像像素计算一个或多个类型的一个或多个特征面。 在图像中定义多个单元，其中每个单元包括第一至第n个像素数，并且图像中每个单元在水平和垂直方向上的起始位置分别是预定水平和垂直步长的整数倍。 为每个单元计算一个或多个类型的一个或多个特征平面求和。 基于特征平面求和的集合来确定图像的图像部分的特征向量，并且将特征向量与对应的对象分类器进行比较，以检测图像的图像部分中相应对象的存在。
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公开(公告)号：US20250021481A1
公开(公告)日：2025-01-16
申请号：US18797945
申请日：2024-08-08
Applicant: Texas Instruments Incorporated
Inventor： Abhijeet Ashok Chachad , Timothy David Anderson , Pramod Kumar Swami , Naveen Bhoria , David Matthew Thompson , Neelima Muralidharan
IPC: G06F12/0811 , G06F12/10
Abstract: An apparatus includes first CPU and second CPU cores, a L1 cache subsystem coupled to the first CPU core and comprising a L1 controller, and a L2 cache subsystem coupled to the L1 cache subsystem and to the second CPU core. The L2 cache subsystem includes a L2 memory and a L2 controller configured to operate in an aliased mode in response to a value in a memory map control register being asserted. In the aliased mode, the L2 controller receives a first request from the first CPU core directed to a virtual address in the L2 memory, receives a second request from the second CPU core directed to the virtual address in the L2 memory, directs the first request to a physical address A in the L2 memory, and directs the second request to a physical address B in the L2 memory.
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公开(公告)号：US12086064B2
公开(公告)日：2024-09-10
申请号：US17847131
申请日：2022-06-22
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Abhijeet Ashok Chachad , Timothy David Anderson , Pramod Kumar Swami , Naveen Bhoria , David Matthew Thompson , Neelima Muralidharan
IPC: G06F12/08 , G06F12/0811 , G06F12/10
CPC classification number: G06F12/0811 , G06F12/10 , G06F2212/608
Abstract: An apparatus includes first CPU and second CPU cores, a L1 cache subsystem coupled to the first CPU core and comprising a L1 controller, and a L2 cache subsystem coupled to the L1 cache subsystem and to the second CPU core. The L2 cache subsystem includes a L2 memory and a L2 controller configured to operate in an aliased mode in response to a value in a memory map control register being asserted. In the aliased mode, the L2 controller receives a first request from the first CPU core directed to a virtual address in the L2 memory, receives a second request from the second CPU core directed to the virtual address in the L2 memory, directs the first request to a physical address A in the L2 memory, and directs the second request to a physical address B in the L2 memory.
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24.发明授权公开(公告)号：US11915431B2
公开(公告)日：2024-02-27
申请号：US16532658
申请日：2019-08-06
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Deepak Kumar Poddar , Anshu Jain , Desappan Kumar , Pramod Kumar Swami
IPC: G06T7/246
CPC classification number: G06T7/246 , G06T2200/28 , G06T2207/20016 , G06T2207/30241
Abstract: A method for sparse optical flow based tracking in a computer vision system is provided that includes detecting feature points in a frame captured by a monocular camera in the computer vision system to generate a plurality of detected feature points, generating a binary image indicating locations of the detected feature points with a bit value of one, wherein all other locations in the binary image have a bit value of zero, generating another binary image indicating neighborhoods of currently tracked points, wherein locations of the neighborhoods in the binary image have a bit value of zero and all other locations in the binary image have a bit value of one, and performing a binary AND of the two binary images to generate another binary image, wherein locations in the binary image having a bit value of one indicate new feature points detected in the frame.
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公开(公告)号：US11876989B2
公开(公告)日：2024-01-16
申请号：US17242433
申请日：2021-04-28
Applicant: Texas Instruments Incorporated
Inventor： Uday Pudipeddi Kiran , Deepak Kumar Poddar , Pramod Kumar Swami , Arun Shankar Kudana
IPC: H04N11/02 , H04N19/423 , H04N19/577 , H04N19/177 , H04N19/44
CPC classification number: H04N19/423 , H04N19/177 , H04N19/44 , H04N19/577
Abstract: Several methods and systems for facilitating multimedia data encoding are disclosed. In an embodiment, a plurality of picture buffers associated with multimedia data are received in an order of capture associated with the plurality of picture buffers. Buffer information is configured for each picture buffer from among the plurality of picture buffers comprising at least one of a metadata associated with the corresponding picture buffer and one or more encoding parameters for the corresponding picture buffer. A provision of picture buffers in an order of encoding is facilitated based on the configured buffer information.
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Patent Agency Ranking
公开(公告)号：US20210150248A1
公开(公告)日：2021-05-20
申请号：US17128365
申请日：2020-12-21
Applicant: Texas Instruments Incorporated
Inventor： Kumar Desappan , Manu Mathew , Pramod Kumar Swami , Praveen Eppa
Abstract: A method for dynamically quantizing feature maps of a received image. The method includes convolving an image based on a predicted maximum value, a predicted minimum value, trained kernel weights and the image data. The input data is quantized based on the predicted minimum value and predicted maximum value. The output of the convolution is computed into an accumulator and re-quantized. The re-quantized value is output to an external memory. The predicted min value and the predicted max value are computed based on the previous max values and min values with a weighted average or a pre-determined formula. Initial min value and max value are computed based on known quantization methods and utilized for initializing the predicted min value and predicted max value in the quantization process.
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27.发明授权公开(公告)号：US11010631B2
公开(公告)日：2021-05-18
申请号：US16730622
申请日：2019-12-30
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Deepak Kumar Poddar , Pramod Kumar Swami , Prashanth Viswanath
Abstract: In accordance with disclosed embodiments, an image processing method includes performing a first scan in a first direction on a first list of pixels in which, for each pixel in the first list, a feature point property is compared with a corresponding feature point property of each of a first set of neighboring pixels, performing a second scan in a second direction on the first list of pixels in which, for each pixel in the first list, a feature point property is compared with a corresponding feature point property of each of a second set of neighboring pixels, using the results of the first and second scans to identify pixels from the first list to be suppressed, and forming a second list of pixels that includes pixels from the first list that are not identified as pixels to be suppressed. The second list represents a non-maxima suppressed list.
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公开(公告)号：US20190124326A1
公开(公告)日：2019-04-25
申请号：US16228350
申请日：2018-12-20
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Soyeb Nagori , Manu Mathew , Pramod Kumar Swami
IPC: H04N19/107 , H04N19/50 , H04N19/176 , H04N19/147
CPC classification number: H04N19/107 , H04N19/147 , H04N19/176 , H04N19/50
Abstract: This invention predicts that intra mode prediction is more effective for the macroblocks where motion estimation in inter mode prediction fails. This failure is indicated by a large value of the inter mode SAD. This invention performs intra mode prediction for only macro blocks have larger inter mode SADs. The definition of a large inter mode SAD differs for different content. This invention compares the inter mode SAD of a current macroblock with an adaptive threshold. This adaptive threshold depends on the average and variance of the SADs of the previous predicted frame. An adaptive threshold is calculated for each new predictive frame.
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29.发明申请公开(公告)号：US20190005349A1
公开(公告)日：2019-01-03
申请号：US15989551
申请日：2018-05-25
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Deepak Kumar Poddar , Pramod Kumar Swami , Prasanth Viswanath
CPC classification number: G06K9/4609 , G06K9/00986 , G06K9/4671 , G06K9/6202
Abstract: This invention transforms a list of feature points in raster scan order into a list of maxima suppressed feature points. A working buffer has two more entries than the width of the original image. Each entry is assigned to an x coordinate of the original image. Each entry stores a combined y coordinate and reliability score for each feature point in the original list. This process involves a forward scan and a backward scan. For each original feature point its x coordinate defines the location within the working buffer where neighbor feature points would be stored if they exist. The working buffer initial data and the y coordinates assure a non-suppress comparison result if the potential neighbors are not actual neighbors. For actual neighbor data, the y coordinates match and the comparison result depends solely upon the relative reliability scores.
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公开(公告)号：US09747515B2
公开(公告)日：2017-08-29
申请号：US14794916
申请日：2015-07-09
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Kumar Desappan , Prashanth R. Viswanath , Pramod Kumar Swami
CPC classification number: G06K9/4671 , G06K9/00973 , G06T7/73 , G06T9/20 , G06T2207/10004 , G06T2207/20164
Abstract: Systems and methods are provided for selecting feature points within an image. A plurality of candidate feature points are identified in the image. A plurality of feature points are selected for each of the plurality of candidate feature points, a plurality of sets of representative pixels. For each set of representative pixels, a representative value is determined as one of a maximum chromaticity value and a minimum chromaticity value from the set of representative pixels. A score is determined for each candidate feature point from the representative values for the plurality of sets of representative pixels associated with the candidate feature point. The feature points are selected according to the determined scores for the plurality of candidate feature points.
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