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公开(公告)号：US20160117569A1
公开(公告)日：2016-04-28
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.
Abstract translation: 提供了用于选择图像内的特征点的系统和方法。 在图像中识别多个候选特征点。 为多个候选特征点中的每一个，多个代表像素组选择多个特征点。 对于每组代表像素，代表值被确定为来自代表像素集合的最大色度值和最小色度值之一。 根据与候选特征点相关联的多组代表性像素的代表值，确定每个候选特征点的得分。 根据多个候选特征点的确定得分来选择特征点。
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公开(公告)号：US11748599B2
公开(公告)日：2023-09-05
申请号：US16797871
申请日：2020-02-21
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Kumar Desappan , Mihir Narendra Mody , Pramod Kumar Swami , Anshu Jain , Rishabh Garg
IPC: G06F12/00 , G06N3/063 , G06T1/60 , G06F12/0804 , G06N3/08
CPC classification number: G06N3/063 , G06F12/0804 , G06N3/08 , G06T1/60
Abstract: Techniques including receiving a first set of values for processing by a machine learning (ML) network, storing a first portion of the first set of values in an on-chip memory, processing the first portion of the first set of values in a first layer of the ML network to generate a second portion of a second set of values, overwriting the stored first portion with the generated second portion, processing the second portion in a second layer of the ML network to generate a third portion of a third set of values, storing the third portion, repeating the steps of storing the first portion, processing the first portion, overwriting the stored first portion, processing the second portion, and storing the third portion for a fourth portion of the first set of values until all portions of the first set of values are processed to generate the third set of values.
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公开(公告)号：US11688078B2
公开(公告)日：2023-06-27
申请号：US17093681
申请日：2020-11-10
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor： Soyeb Noormohammed Nagori , Manu Mathew , Kumar Desappan , Pramod Kumar Swami
CPC classification number: G06T7/20 , G06T7/70 , G06T2207/10016
Abstract: A method for video object detection includes detecting an object in a first video frame, and selecting a first interest point and a second interest point of the object. The first interest point is in a first region of interest located at a first corner of a box surrounding the object. The second interest point is in a second region of interest located at a second corner of the box. The second corner is diagonally opposite the first corner. A first optical flow of the first interest point and a second optical flow of the second interest point are determined. A location of the object in a second video frame is estimated by determining, in the second video frame, a location of the first interest point based on the first optical flow and a location of the second interest point based on the second optical flow.
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14.发明申请公开(公告)号：US20220321905A1
公开(公告)日：2022-10-06
申请号：US17844739
申请日：2022-06-21
Applicant: Texas Instruments Incorporated
Inventor： Soyeb Nagori , Arun Shankar Kudana , Pramod Kumar Swami
IPC: H04N19/523 , H04N19/105 , H04N19/176 , H04N19/147 , H04N19/172 , H04N19/61 , H04N19/109 , H04N19/114 , H04N19/117 , H04N19/156 , H04N19/157
Abstract: Several techniques aimed at reducing computational complexity when encoding uses bi-predictively encoded frames (B-frames) are implemented in a video encoder. In an embodiment, B-frames are not used as reference frames for encoding P-frames and other B-frames. Non-use of B-frames allows a de-blocking filter used in the video encoder to be switched off when reconstructing encoded B-frames, and use of a lower complexity filter for fractional-resolution motion search for B-frames. In another embodiment, cost functions used in motion estimation for B-frames are simplified to reduce computational complexity. In one more embodiment, fractional pixel refinement in motion search for B-frames is simplified. In yet another embodiment, predictors used in motion estimation for a macro-block in a P-frame are selected from a B-frame that uses a same reference frame as the P-frame.
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公开(公告)号：US20210250595A1
公开(公告)日：2021-08-12
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: H04N19/423 , H04N19/577 , H04N19/177 , H04N19/44
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
16.发明申请公开(公告)号：US20200236394A1
公开(公告)日：2020-07-23
申请号：US16838115
申请日：2020-04-02
Applicant: Texas Instruments Incorporated
Inventor： Soyeb Nagori , Arun Shankar Kudana , Pramod Kumar Swami
IPC: H04N19/523 , H04N19/157 , H04N19/156 , H04N19/117 , H04N19/114 , H04N19/109 , H04N19/61 , H04N19/172 , H04N19/147 , H04N19/176 , H04N19/105
Abstract: Several techniques aimed at reducing computational complexity when encoding uses bi-predictively encoded frames (B-frames) are implemented in a video encoder. In an embodiment, B-frames are not used as reference frames for encoding P-frames and other B-frames. Non-use of B-frames allows a de-blocking filter used in the video encoder to be switched off when reconstructing encoded B-frames, and use of a lower complexity filter for fractional-resolution motion search for B-frames. In another embodiment, cost functions used in motion estimation for B-frames are simplified to reduce computational complexity. In one more embodiment, fractional pixel refinement in motion search for B-frames is simplified. In yet another embodiment, predictors used in motion estimation for a macro-block in a P-frame are selected from a B-frame that uses a same reference frame as the P-frame.
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公开(公告)号：US10102445B2
公开(公告)日：2018-10-16
申请号：US15688458
申请日：2017-08-28
Applicant: Texas Instruments Incorporated
Inventor： Kumar Desappan , Prashanth R. Viswanath , Pramod Kumar Swami
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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18.发明申请公开(公告)号：US20180035128A1
公开(公告)日：2018-02-01
申请号：US15728138
申请日：2017-10-09
Applicant: Texas Instruments Incorporated
Inventor： Soyeb Nagori , Arun Shankar Kudana , Pramod Kumar Swami
IPC: H04N19/523 , H04N19/176 , H04N19/172 , H04N19/157 , H04N19/156 , H04N19/147 , H04N19/117 , H04N19/114 , H04N19/109 , H04N19/61 , H04N19/105
CPC classification number: H04N19/523 , H04N19/105 , H04N19/109 , H04N19/114 , H04N19/117 , H04N19/147 , H04N19/156 , H04N19/157 , H04N19/172 , H04N19/176 , H04N19/61
Abstract: Several techniques aimed at reducing computational complexity when encoding uses bi-predictively encoded frames (B-frames) are implemented in a video encoder. In an embodiment, B-frames are not used as reference frames for encoding P-frames and other B-frames. Non-use of B-frames allows a de-blocking filter used in the video encoder to be switched off when reconstructing encoded B-frames, and use of a lower complexity filter for fractional-resolution motion search for B-frames. In another embodiment, cost functions used in motion estimation for B-frames are simplified to reduce computational complexity. In one more embodiment, fractional pixel refinement in motion search for B-frames is simplified. In yet another embodiment, predictors used in motion estimation for a macro-block in a P-frame are selected from a B-frame that uses a same reference frame as the P-frame.
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公开(公告)号：US20170357874A1
公开(公告)日：2017-12-14
申请号：US15688458
申请日：2017-08-28
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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20.发明申请公开(公告)号：US20170193669A1
公开(公告)日：2017-07-06
申请号：US15266149
申请日：2016-09-15
Applicant: Texas Instruments Incorporated
Inventor： Deepak Kumar Poddar , Anshu Jain , Desappan Kumar , Pramod Kumar Swami
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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