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    IMAGE-BASED THREE-DIMENSIONAL OCCUPANT ASSESSMENT FOR IN-CABIN MONITORING SYSTEMS AND APPLICATIONS
    23.
    发明申请
    IMAGE-BASED THREE-DIMENSIONAL OCCUPANT ASSESSMENT FOR IN-CABIN MONITORING SYSTEMS AND APPLICATIONS 有权

    公开(公告)号：US20250022290A1

    公开(公告)日：2025-01-16

    申请号：US18349853

    申请日：2023-07-10

    Applicant: NVIDIA Corporation

    Inventor： Sakthivel SIVARAMAN ,  Arjun Guru ,  Rajath Shetty ,  Umar Iqbal ,  Orazio Gallo ,  Hang Su ,  Abhishek Badki ,  Varsha Hedau

    IPC: G06V20/59 ,  G06T7/50 ,  G06T17/00

    Abstract: In various examples, image-based three-dimensional occupant assessment for in-cabin monitoring systems and applications are provided. An evaluation function may determine a 3D representation of an occupant of a machine by evaluating sensor data comprising an image frame from an optical image sensor. The 3D representation may comprise at least one characteristic representative of a size of the occupant, (e.g., a 3D pose and/or 3D shape), which may be used to derive other characteristics such as, but not limited to weight, height, and/or age. A first processing path may generate a representation of one or more features corresponding to at least a portion of the occupant based on optical image data, and a second processing path may determine a depth corresponding to the one or more features based on depth data derived from the optical image data and ground truth depth data corresponding to the interior of the machine.

    Deep-learning method for separating reflection and transmission images visible at a semi-reflective surface in a computer image of a real-world scene
    24.
    发明授权
    Deep-learning method for separating reflection and transmission images visible at a semi-reflective surface in a computer image of a real-world scene 有权

    公开(公告)号：US11270161B2

    公开(公告)日：2022-03-08

    申请号：US16924005

    申请日：2020-07-08

    Applicant: NVIDIA Corporation

    Inventor： Orazio Gallo ,  Jinwei Gu ,  Jan Kautz ,  Patrick Wieschollek

    IPC: G06K9/00 ,  G06K9/62

    Abstract: When a computer image is generated from a real-world scene having a semi-reflective surface (e.g. window), the computer image will create, at the semi-reflective surface from the viewpoint of the camera, both a reflection of a scene in front of the semi-reflective surface and a transmission of a scene located behind the semi-reflective surface. Similar to a person viewing the real-world scene from different locations, angles, etc., the reflection and transmission may change, and also move relative to each other, as the viewpoint of the camera changes. Unfortunately, the dynamic nature of the reflection and transmission negatively impacts the performance of many computer applications, but performance can generally be improved if the reflection and transmission are separated. The present disclosure uses deep learning to separate reflection and transmission at a semi-reflective surface of a computer image generated from a real-world scene.

    Image generation of a three-dimensional scene using multiple focal lengths
    26.
    发明授权
    Image generation of a three-dimensional scene using multiple focal lengths 有权

    公开(公告)号：US10212406B2

    公开(公告)日：2019-02-19

    申请号：US15381010

    申请日：2016-12-15

    Applicant: NVIDIA Corporation

    Inventor： Orazio Gallo ,  Jan Kautz ,  Abhishek Haridas Badki

    IPC: H04N5/232 ,  H04N13/111 ,  H04N13/128 ,  H04N13/271

    Abstract: A system and method for computational zoom generates a resulting image having two or more effective focal lengths. A first surface within a three-dimensional (3D) scene including a first and second set of 3D objects defined by 3D information is identified. The first and second sets of 3D objects are located within first and second depth ranges of the 3D scene, respectively. The first set of 3D objects is projected onto the first surface according to a first projection mapping to produce a first portion of image components. The second set of 3D objects is projected onto the first surface according to a second projection mapping to produce a second portion of image components. The resulting image comprising the first portion of image components and the second portion of image components is generated based on a camera projection from the first surface to a camera view plane.

    SYSTEMS AND METHODS FOR COMPUTATIONAL ZOOM
    27.
    发明申请
    SYSTEMS AND METHODS FOR COMPUTATIONAL ZOOM 审中-公开

    公开(公告)号：US20180176532A1

    公开(公告)日：2018-06-21

    申请号：US15381010

    申请日：2016-12-15

    Applicant: NVIDIA Corporation

    Inventor： Orazio Gallo ,  Jan Kautz ,  Abhishek Haridas Badki

    IPC: H04N13/00 ,  H04N5/232 ,  H04N13/02

    CPC classification number: H04N13/111 ,  H04N5/23216 ,  H04N5/23296 ,  H04N13/128 ,  H04N13/271

    Abstract: A system and method for computational zoom generates a resulting image having two or more effective focal lengths. A first surface within a three-dimensional (3D) scene including a first and second set of 3D objects defined by 3D information is identified. The first and second sets of 3D objects are located within first and second depth ranges of the 3D scene, respectively. The first set of 3D objects is projected onto the first surface according to a first projection mapping to produce a first portion of image components. The second set of 3D objects is projected onto the first surface according to a second projection mapping to produce a second portion of image components. The resulting image comprising the first portion of image components and the second portion of image components is generated based on a camera projection from the first surface to a camera view plane.

    Unified optimization method for end-to-end camera image processing for translating a sensor captured image to a display image
    28.
    发明授权
    Unified optimization method for end-to-end camera image processing for translating a sensor captured image to a display image 有权
    用于将传感器拍摄图像转换为显示图像的端到端相机图像处理的统一优化方法

    公开(公告)号：US09558712B2

    公开(公告)日：2017-01-31

    申请号：US14600507

    申请日：2015-01-20

    Applicant: NVIDIA Corporation

    Inventor： Dawid Stanislaw Pajak ,  Felix Heide ,  Nagilla Dikpal Reddy ,  Mushfiqur Rouf ,  Jan Kautz ,  Kari Pulli ,  Orazio Gallo

    IPC: G09G5/02 ,  G09G5/36 ,  G06T5/00

    CPC classification number: G09G5/02 ,  G06T3/4015 ,  G06T5/001 ,  G06T5/002 ,  G09G5/026 ,  G09G5/363 ,  G09G2320/0238 ,  G09G2320/0242 ,  G09G2320/0247 ,  G09G2320/066 ,  G09G2360/08

    Abstract: A computer implemented method of determining a latent image from an observed image is disclosed. The method comprises implementing a plurality of image processing operations within a single optimization framework, wherein the single optimization framework comprises solving a linear minimization expression. The method further comprises mapping the linear minimization expression onto at least one non-linear solver. Further, the method comprises using the non-linear solver, iteratively solving the linear minimization expression in order to extract the latent image from the observed image, wherein the linear minimization expression comprises: a data term, and a regularization term, and wherein the regularization term comprises a plurality of non-linear image priors.

    Abstract translation: 公开了一种从观察图像确定潜像的计算机实现方法。 该方法包括在单个优化框架内实现多个图像处理操作，其中单个优化框架包括求解线性最小化表达式。 该方法还包括将线性最小化表达映射到至少一个非线性求解器上。 此外，该方法包括使用非线性求解器，迭代地求解线性最小化表达以从观察图像中提取潜像，其中线性最小化表达式包括：数据项和正则化项，其中正则化 术语包括多个非线性图像先验。

    PHYSIOLOGICALLY BASED ADAPTIVE IMAGE GENERATION
    29.
    发明申请
    PHYSIOLOGICALLY BASED ADAPTIVE IMAGE GENERATION 有权
    基于生理学的自适应图像生成

    公开(公告)号：US20150346817A1

    公开(公告)日：2015-12-03

    申请号：US14722036

    申请日：2015-05-26

    Applicant: NVIDIA CORPORATION

    Inventor： Orazio Gallo ,  Kari Antero Pulli ,  David Edward Jacobs

    IPC: G06F3/01 ,  G09G5/10

    CPC classification number: G09G5/10 ,  G09G5/02 ,  G09G2320/0257 ,  G09G2320/066 ,  G09G2354/00

    Abstract: A system, computer-readable medium, and method are provided for generating images based on adaptations of the human visual system. An input image is received, an effect provoking change is received, and an afterimage resulting from a cumulative effect of human visual adaptation is computed based on the effect provoking change and a per-photoreceptor type physiological adaptation of the human visual system. The computed afterimage may include a bleaching afterimage effect and/or a local adaptation afterimage effect. The computed afterimage is then accumulated into an output image for display.

    Abstract translation: 提供了一种基于人类视觉系统的适应性来生成图像的系统，计算机可读介质和方法。 接收输入图像，接收到效果发生变化，并且基于人类视觉系统的效果发生变化和每个感光体类型的生理适应来计算由人类视觉适应的累积效应产生的残像。 计算的残影可以包括漂白余像效应和/或局部适应余像效果。 然后将计算出的残像积累到输出图像中进行显示。

    System, method, and computer program product for performing fast, non-rigid registration for high dynamic range image stacks
    30.
    发明授权
    System, method, and computer program product for performing fast, non-rigid registration for high dynamic range image stacks 有权
    用于高动态范围图像堆栈执行快速，非刚性配准的系统，方法和计算机程序产品

    公开(公告)号：US09153027B2

    公开(公告)日：2015-10-06

    申请号：US14070399

    申请日：2013-11-01

    Applicant: NVIDIA Corporation

    Inventor： Orazio Gallo ,  Kari Antero Pulli ,  Jun Hu

    IPC: G06K9/40 ,  G06T7/00 ,  G06T3/00

    CPC classification number: G06T7/003 ,  G06T3/0068 ,  G06T7/33 ,  G06T7/35 ,  G06T2207/10016 ,  G06T2207/20208 ,  G06T2207/20221

    Abstract: A system, method, and computer program product are provided for performing fast, non-rigid registration for at least two images of a high-dynamic range image stack. The method includes the steps of generating a warped image based on a set of corresponding pixels, analyzing the warped image to detect unreliable pixels in the warped image, and generating a corrected pixel value for each unreliable pixel in the warped image. The set of corresponding pixels includes a plurality of pixels in a source image, each pixel in the plurality of pixels associated with a potential feature in the source image and paired with a corresponding pixel in a reference image that substantially matches the pixel in the source image.

    Abstract translation: 提供了一种系统，方法和计算机程序产品，用于对高动态范围图像堆叠的至少两个图像执行快速，非刚性配准。 该方法包括以下步骤：基于一组对应的像素产生翘曲图像，分析扭曲图像以检测翘曲图像中的不可靠像素;以及为扭曲图像中的每个不可靠像素生成经校正的像素值。 相应像素的集合包括源图像中的多个像素，多个像素中的每个像素与源图像中的潜在特征相关联，并与基本匹配源图像中的像素的参考图像中的对应像素配对 。

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