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公开(公告)号:US20170193311A1
公开(公告)日:2017-07-06
申请号:US15346491
申请日:2016-11-08
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor: DEEPAK KUMAR PODDAR , SHYAM JAGANNATHAN , SOYEB NAGORI , PRAMOD KUMAR SWAMI
CPC classification number: G06K9/00791 , G05D1/0253 , G05D2201/0213 , G06F9/30007 , G06F15/8007 , G06K9/52 , G06T3/4038
Abstract: A vehicular structure from motion (SfM) system can include an input to receive a sequence of image frames acquired from a camera on a vehicle and an SIMD processor to process 2D feature point input data extracted from the image frames so as to compute 3D points. For a given 3D point, the SfM system can calculate partial ATA and partial ATb matrices outside of an iterative triangulation loop, reducing computational complexity inside the loop. Multiple tracks can be processed together to take full advantage of SIMD instruction parallelism.
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公开(公告)号:US20230206604A1
公开(公告)日:2023-06-29
申请号:US18176699
申请日:2023-03-01
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor: DEEPAK KUMAR PODDAR , SOYEB NAGORI , HRUSHIKESH TUKARAM GARUD , KUMAR DESAPPAN
CPC classification number: G06V10/7715 , G06T3/4046 , G06V10/48 , G06V10/462 , G06N3/084
Abstract: An example image feature extraction system comprises an encoder neural network having a first set of layers and a decoder neural network having a second set of layers and a third set of layers. The encoder neural network receives an input image, processes the input image through the first set of layers, and computes an encoded feature map based on the input image. The decoder neural network receives the encoded feature map, processes the encoded feature map through the second set of layers to compute a keypoint score map, and processes the encoded feature map through at least a portion of the third set of layers to compute a feature description map.
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公开(公告)号:US20220180476A1
公开(公告)日:2022-06-09
申请号:US17112096
申请日:2020-12-04
Applicant: TEXAS INSTRUMENTS INCORPORATED
Inventor: DEEPAK KUMAR PODDAR , SOYEB NAGORI , HRUSHIKESH TUKARAM GARUD , KUMAR DESAPPAN
Abstract: This description relates to image feature extraction. In some examples, a system can include a keypoint detector and a feature list generator. The keypoint detector can be configured to upsample a keypoint score map to produce an upsampled keypoint score map. The keypoint score map can include feature scores indicative of a likelihood of at least one feature being present at keypoints in an image. The feature list generator can be configured to identify a subset of keypoints of the keypoints in the image using the feature scores of the up sampled keypoint score map, determine descriptors for the subset of keypoints based on a feature description map, and generate a keypoint descriptor map for the image based on the determined descriptors.
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