Patents by Inventor Hrushikesh Tukaram Garud
Hrushikesh Tukaram Garud has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20240078284Abstract: A hardware accelerator is configured to perform matrix multiplication and/or additional operations to optimize keypoint matching. A sum of squared error (SSE) calculation may be determined by utilizing the hardware accelerator to perform matrix multiplication to obtain a cost matrix for two sets of keypoint descriptors from two images. The hardware accelerator may determine a best cost calculation for each keypoint in each direction, which is utilized to perform keypoint matching.Type: ApplicationFiled: November 1, 2023Publication date: March 7, 2024Inventors: Deepak Kumar PODDAR, Soyeb NAGORI, Hrushikesh Tukaram GARUD, Pramod Kumar SWAMI
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Patent number: 11891091Abstract: An example driver assistance system includes an object detection (OD) network, a semantic segmentation network, a processor, and a memory. In an example method, an image is received and stored in the memory. An object detection (OD) polygon is generated for each object detected in the image, and each OD polygon encompasses at least a portion of the corresponding object detected in the image. A region of interest (ROI) is associated with each OD polygon. Such method may further comprise generating a mask for each ROI, each mask configured as a bitmap approximating a size of the corresponding ROI; generating at least one boundary polygon for each mask based on the corresponding mask, each boundary polygon having multiple vertices and enclosing the corresponding mask; and reducing a number of vertices of the boundary polygons based on a comparison between points of the boundary polygons and respective points on the bitmaps.Type: GrantFiled: February 22, 2023Date of Patent: February 6, 2024Assignee: Texas Instruments IncorporatedInventors: Soyeb Noormohammed Nagori, Deepak Poddar, Hrushikesh Tukaram Garud
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Patent number: 11887346Abstract: 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.Type: GrantFiled: March 1, 2023Date of Patent: January 30, 2024Assignee: Texas Instruments IncorporatedInventors: Deepak Kumar Poddar, Soyeb Nagori, Hrushikesh Tukaram Garud, Kumar Desappan
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Publication number: 20240007648Abstract: The disclosure provides a sample adaptive offset (SAO) encoder. The SAO encoder includes a statistics collection (SC) block and a rate distortion optimization (RDO) block coupled to the SC block. The SC block receives a set of deblocked pixels and a set of original pixels. The SC block categorizes each deblocked pixel of the set of deblocked pixels in at least one of a plurality of band and edge categories. The SC block estimates an error in each category as difference between a deblocked pixel of the set of deblocked pixels and corresponding original pixel of the set of original pixels. The RDO block determines a set of candidate offsets associated with each category and selects a candidate offset with a minimum RD cost. The minimum RD cost is used by a SAO type block and a decision block to generate final offsets for the SAO encoder.Type: ApplicationFiled: September 18, 2023Publication date: January 4, 2024Inventors: Hrushikesh Tukaram Garud, Mihir Narendra Mody, Soyeb Nagori
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Patent number: 11847184Abstract: A matching accelerator in the form of a hardware accelerator configured to perform matrix multiplication and/or additional operations is used to optimize keypoint matching. An SSE calculation may be determined by utilizing the matching accelerator to perform matrix multiplication to obtain a cost matrix for two sets of keypoint descriptors from two images. The hardware accelerator may determine a best cost calculation for each keypoint in each direction, which is utilized to perform keypoint matching.Type: GrantFiled: January 14, 2021Date of Patent: December 19, 2023Assignee: Texas Instruments IncorporatedInventors: Deepak Kumar Poddar, Soyeb Nagori, Hrushikesh Tukaram Garud, Pramod Kumar Swami
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Patent number: 11765359Abstract: The disclosure provides a sample adaptive offset (SAO) encoder. The SAO encoder includes a statistics collection (SC) block and a rate distortion optimization (RDO) block coupled to the SC block. The SC block receives a set of deblocked pixels and a set of original pixels. The SC block categorizes each deblocked pixel of the set of deblocked pixels in at least one of a plurality of band and edge categories. The SC block estimates an error in each category as difference between a deblocked pixel of the set of deblocked pixels and corresponding original pixel of the set of original pixels. The RDO block determines a set of candidate offsets associated with each category and selects a candidate offset with a minimum RD cost. The minimum RD cost is used by a SAO type block and a decision block to generate final offsets for the SAO encoder.Type: GrantFiled: March 25, 2021Date of Patent: September 19, 2023Assignee: Texas Instruments IncorporatedInventors: Hrushikesh Tukaram Garud, Mihir Narendra Mody, Soyeb Nagori
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Publication number: 20230206604Abstract: 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.Type: ApplicationFiled: March 1, 2023Publication date: June 29, 2023Inventors: DEEPAK KUMAR PODDAR, SOYEB NAGORI, HRUSHIKESH TUKARAM GARUD, KUMAR DESAPPAN
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Publication number: 20230202524Abstract: An example driver assistance system includes an object detection (OD) network, a semantic segmentation network, a processor, and a memory. In an example method, an image is received and stored in the memory. An object detection (OD) polygon is generated for each object detected in the image, and each OD polygon encompasses at least a portion of the corresponding object detected in the image. A region of interest (ROI) is associated with each OD polygon. Such method may further comprise generating a mask for each ROI, each mask configured as a bitmap approximating a size of the corresponding ROI; generating at least one boundary polygon for each mask based on the corresponding mask, each boundary polygon having multiple vertices and enclosing the corresponding mask; and reducing a number of vertices of the boundary polygons based on a comparison between points of the boundary polygons and respective points on the bitmaps.Type: ApplicationFiled: February 22, 2023Publication date: June 29, 2023Inventors: Soyeb Noormohammed Nagori, Deepak Poddar, Hrushikesh Tukaram Garud
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Patent number: 11620478Abstract: In described examples, an apparatus includes an object detection (OD) network that is configured to generate OD polygons in response to a received at least one camera image and a semantic segmentation (SS) network that is configured to generate SS data in response to the received at least one camera image. A processor is configured to generate an updated occupancy grid in response to the OD polygons and the SS data. A vehicle is optionally configured to respond to a driving action generated in response to the updated occupancy grid.Type: GrantFiled: February 6, 2020Date of Patent: April 4, 2023Assignee: Texas Instruments IncorporatedInventors: Soyeb Noormohammed Nagori, Deepak Poddar, Hrushikesh Tukaram Garud
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Patent number: 11615612Abstract: 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.Type: GrantFiled: December 4, 2020Date of Patent: March 28, 2023Assignee: Texas Instruments IncorporatedInventors: Deepak Kumar Poddar, Soyeb Nagori, Hrushikesh Tukaram Garud, Kumar Desappan
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Publication number: 20220392108Abstract: Techniques for localizing a vehicle include obtaining an image from a camera, identifying a set of image feature points in the image, obtaining an approximate location of the vehicle, determining a set of sub-volumes (SVs) of a map to access based on the approximate location, obtaining map feature points and associated map feature descriptors associated with the set of SVs, determining a set of candidate matches between the set of image feature points and the obtained map feature points, determining a set of potential poses of the camera from candidate matches from the set of candidate matches and an associated reprojection error estimated for remaining points to select a first pose of the set of potential poses having a lowest associated reprojection error, determining the first pose is within a threshold value of an expected vehicle location, and outputting a vehicle location based on the first pose.Type: ApplicationFiled: August 15, 2022Publication date: December 8, 2022Inventors: Hrushikesh Tukaram GARUD, Deepak PODDAR, Soyeb Noormohammed NAGORI
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Publication number: 20220375022Abstract: A computer vision system is provided that includes a camera capture component configured to capture an image from a camera, a memory, and an image compression decompression engine (ICDE) coupled to the memory and configured to receive each line of the image, and compress each line to generate a compressed bit stream. To compress a line, the ICDE is configured to divide the line into compression units, and compress each compression unit, wherein to compress a compression unit, the ICDE is configured to perform delta prediction on the compression unit to generate a delta predicted compression unit, compress the delta predicted compression unit using exponential Golomb coding to generate a compressed delta predicted compression unit, and add the compressed delta predicted compression unit to the compressed bit stream.Type: ApplicationFiled: August 2, 2022Publication date: November 24, 2022Inventors: Hrushikesh Tukaram Garud, Ankit Ajmani, Soyeb Noormohammed Nagori, Mihir Narendra Mody
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Patent number: 11417017Abstract: Techniques for localizing a vehicle including obtaining an image from a camera, identifying a set of image feature points in the image, obtaining an approximate location of the vehicle, determining a set of sub-volumes (SVs) of a map to access based on the approximate location, obtaining map feature points and associated map feature descriptors associated with the set of SVs, determining a set of candidate matches between the set of image feature points and the obtained map feature points, determining a set of potential poses of the camera from candidate matches from the set of candidate matches and an associated reprojection error estimated for remaining points to select a first pose of the set of potential poses having a lowest associated reprojection error, determining the first pose is within a threshold value of an expected vehicle location, and outputting a vehicle location based on the first pose.Type: GrantFiled: April 21, 2020Date of Patent: August 16, 2022Assignee: Texas Instmments IncorporatedInventors: Hrushikesh Tukaram Garud, Deepak Poddar, Soyeb Noormohammed Nagori
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Patent number: 11410265Abstract: A computer vision system is provided that includes a camera capture component configured to capture an image from a camera, a memory, and an image compression decompression engine (ICDE) coupled to the memory and configured to receive each line of the image, and compress each line to generate a compressed bit stream. To compress a line, the ICDE is configured to divide the line into compression units, and compress each compression unit, wherein to compress a compression unit, the ICDE is configured to perform delta prediction on the compression unit to generate a delta predicted compression unit, compress the delta predicted compression unit using exponential Golomb coding to generate a compressed delta predicted compression unit, and add the compressed delta predicted compression unit to the compressed bit stream.Type: GrantFiled: April 25, 2020Date of Patent: August 9, 2022Assignee: TEXAS INSTRUMENTS INCORPORATEDInventors: Hrushikesh Tukaram Garud, Ankit Ajmani, Soyeb Noormohammed Nagori, Mihir Narendra Mody
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Publication number: 20220180476Abstract: 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.Type: ApplicationFiled: December 4, 2020Publication date: June 9, 2022Inventors: DEEPAK KUMAR PODDAR, SOYEB NAGORI, HRUSHIKESH TUKARAM GARUD, KUMAR DESAPPAN
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Patent number: 11341750Abstract: An image processing system includes a processor and optical flow (OF) determination logic for quantifying relative motion of a feature present in a first frame of video and a second frame of video that provide at least one of temporally and spatially ordered images with respect to the two frames of video. The OF determination logic configures the processor to implement performing OF estimation between the first frame and second frame using a pyramidal block matching (PBM) method to generate an initial optical flow (OF) estimate at a base pyramid level having integer pixel resolution, and refining the initial OF estimate using at least one pass of a modified Lucas-Kanade (LK) method to provide a revised OF estimate having fractional pixel resolution.Type: GrantFiled: February 5, 2019Date of Patent: May 24, 2022Assignee: TEXAS INSTRUMENTS INCORPORATEDInventors: Hrushikesh Tukaram Garud, Manu Mathew, Soyeb Noormohammed Nagori
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Publication number: 20210256293Abstract: A matching accelerator in the form of a hardware accelerator configured to perform matrix multiplication and/or additional operations is used to optimize keypoint matching. An SSE calculation may be determined by utilizing the matching accelerator to perform matrix multiplication to obtain a cost matrix for two sets of keypoint descriptors from two images. The hardware accelerator may determine a best cost calculation for each keypoint in each direction, which is utilized to perform keypoint matching.Type: ApplicationFiled: January 14, 2021Publication date: August 19, 2021Inventors: Deepak Kumar PODDAR, Soyeb NAGORI, Hrushikesh Tukaram GARUD, Pramod Kumar SWAMI
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Publication number: 20210211680Abstract: The disclosure provides a sample adaptive offset (SAO) encoder. The SAO encoder includes a statistics collection (SC) block and a rate distortion optimization (RDO) block coupled to the SC block. The SC block receives a set of deblocked pixels and a set of original pixels. The SC block categorizes each deblocked pixel of the set of deblocked pixels in at least one of a plurality of band and edge categories. The SC block estimates an error in each category as difference between a deblocked pixel of the set of deblocked pixels and corresponding original pixel of the set of original pixels. The RDO block determines a set of candidate offsets associated with each category and selects a candidate offset with a minimum RD cost. The minimum RD cost is used by a SAO type block and a decision block to generate final offsets for the SAO encoder.Type: ApplicationFiled: March 25, 2021Publication date: July 8, 2021Inventors: Hrushikesh Tukaram Garud, Mihir Narendra Mody, Soyeb Nagori
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Patent number: 11006124Abstract: The disclosure provides a sample adaptive offset (SAO) encoder. The SAO encoder includes a statistics collection (SC) block and a rate distortion optimization (RDO) block coupled to the SC block. The SC block receives a set of deblocked pixels and a set of original pixels. The SC block categorizes each deblocked pixel of the set of deblocked pixels in at least one of a plurality of band and edge categories. The SC block estimates an error in each category as difference between a deblocked pixel of the set of deblocked pixels and corresponding original pixel of the set of original pixels. The RDO block determines a set of candidate offsets associated with each category and selects a candidate offset with a minimum RD cost. The minimum RD cost is used by a SAO type block and a decision block to generate final offsets for the SAO encoder.Type: GrantFiled: June 2, 2020Date of Patent: May 11, 2021Assignee: TEXAS INSTRUMENTS INCORPORATEDInventors: Hrushikesh Tukaram Garud, Mihir Narendra Mody, Soyeb Nagori
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Publication number: 20200334857Abstract: Techniques for localizing a vehicle are provided that include obtaining an image from a camera, identifying a set of image feature points in the image, obtaining an approximate location of the vehicle, determining a set of sub-volumes (SVs) of a map to access based on the approximate location, obtaining map feature points and associated map feature descriptors associated with the set of SVs, determining a set of candidate matches between the set of image feature points and the obtained map feature points, determining a set of potential poses of the camera from candidate matches from the set of candidate matches and an associated reprojection error estimated for remaining points to select a first pose of the set of potential poses having a lowest associated reprojection error, determining the first pose is within a threshold value of an expected vehicle location, and outputting a vehicle location based on the first pose.Type: ApplicationFiled: April 21, 2020Publication date: October 22, 2020Inventors: Hrushikesh Tukaram GARUD, Deepak PODDAR, Soyeb Noormohammed NAGORI