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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：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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