Gordon Stein, CFO of CleanTech Lithium, explains why CTL acquired the 23 Laguna Verde licenses. Watch the video here.
London South East prides itself on its community spirit, and in order to keep the chat section problem free, we ask all members to follow these simple rules. In these rules, we refer to ourselves as "we", "us", "our". The user of the website is referred to as "you" and "your".
By posting on our share chat boards you are agreeing to the following:
The IP address of all posts is recorded to aid in enforcing these conditions. As a user you agree to any information you have entered being stored in a database. You agree that we have the right to remove, edit, move or close any topic or board at any time should we see fit. You agree that we have the right to remove any post without notice. You agree that we have the right to suspend your account without notice.
Please note some users may not behave properly and may post content that is misleading, untrue or offensive.
It is not possible for us to fully monitor all content all of the time but where we have actually received notice of any content that is potentially misleading, untrue, offensive, unlawful, infringes third party rights or is potentially in breach of these terms and conditions, then we will review such content, decide whether to remove it from this website and act accordingly.
Premium Members are members that have a premium subscription with London South East. You can subscribe here.
London South East does not endorse such members, and posts should not be construed as advice and represent the opinions of the authors, not those of London South East Ltd, or its affiliates.
Correction.
Ford 2019-11-14/ Toyota 2019-11-21 / GM 2019-11-28 patents all describe distortion analysis and rectification.
'Unprecedented Collaboration' or JConfirmation Bias ? you decide.
FORD GLOBAL TECH LLC 2019-11-14
DISTORTION CORRECTION FOR VEHICLE SURROUND VIEW CAMERA PROJECTIONS
Method and apparatus are disclosed for distortion correction for vehicle surround view camera projections. An example vehicle includes cameras to capture images of a perimeter around the vehicle and a processor. The processor, using the images, generates a composite image of an area around the vehicle, and generates a depth map that defines spatial relationships between the vehicle and objects around the vehicle. The processor also generates a projection surface using the depth map. Additionally, the processor presents an interface for generating a view image based on the composite image projected onto the projection surface.
https://worldwide.espacenet.com/publicationDetails/biblio?II=3&ND=3&adjacent=true&locale=en_EP&FT=D&date=20191114&CC=US&NR=2019349571A1&KC=A1#
Ford 2019-11-21/ Toyota 2019-11-21 / GM 2019-11-28 patents all describe distortion analysis and rectification.
'Unprecedented Collaboration' or JConfirmation Bias ? you decide.
FORD GLOBAL TECH LLC 2019-11-14
DISTORTION CORRECTION FOR VEHICLE SURROUND VIEW CAMERA PROJECTIONS
Method and apparatus are disclosed for distortion correction for vehicle surround view camera projections. An example vehicle includes cameras to capture images of a perimeter around the vehicle and a processor. The processor, using the images, generates a composite image of an area around the vehicle, and generates a depth map that defines spatial relationships between the vehicle and objects around the vehicle. The processor also generates a projection surface using the depth map. Additionally, the processor presents an interface for generating a view image based on the composite image projected onto the projection surface.
https://worldwide.espacenet.com/publicationDetails/biblio?II=3&ND=3&adjacent=true&locale=en_EP&FT=D&date=20191114&CC=US&NR=2019349571A1&KC=A1#
'Unprecedented Collaboration' or JConfirmation Bias ? you decide.
Toyota
SYSTEMS AND METHODS OF PROCESSING AN IMAGE 2019-11-21
https://worldwide.espacenet.com/publicationDetails/biblio?II=6&ND=3&adjacent=true&locale=en_EP&FT=D&date=20191121&CC=US&NR=2019354780A1&KC=A1#
Systems, methods, and other embodiments described herein relate to processing an image having a distortion and an object. The method according to some embodiments includes acquiring an image having a distortion and performing a first object detection analysis on a first portion of the image. Next, the method includes performing an undistortion process on the image, and after, performing a second object detection analysis on a second portion of the image. The second portion of the image is different than the first portion of the image. The method can then combine a first result of the first object detection analysis with a second result of the second object detection analysis.
GM 2019-11-28
CONTROL SYSTEMS, CONTROL PROCEDURES AND CONTROLS FOR AN AUTONOMOUS VEHICLE
[0035]
Cameras (or image sensors) may be arranged to provide a three hundred and sixty (360) degree image coverage of the surroundings of the vehicle 10. The cameras capture images (eg. B. frames) and give image data (z. A distorted image in YUV format), which can then be processed into rectified (or undistorted) camera images. An image pre-processing module can process the image data by equalizing / correcting the image data, pre-processing the corrected image data (e.g. B. image size change and average subtraction) and the corrected, preprocessed image data in corrected camera images (z. In a normal RGB format) that can classify a neural network of an image classification module. The image data may be corrected to correct for distortions in the image, which may cause straight lines (in reality) to appear curved, for example, when point clouds in 3D space were projected onto the uncorrected image data, they might actually become distorted due to the distortions be the wrong place in the picture.
By equalizing the image, the projections from the 3D space correspond to the correct parts of the image. The rectified camera images may then be sent to an image classification module along with other inputs, including three-dimensional locations of objects from an object tracking module, and processed to generate the image classification data that may be provided to an object classification module and used to generate object classification data that is then sent to an object tracking module which processes the objects, radar tracking information and object classification data to generate object tracking information.
https://worldwide.espacenet.com/publicationDetails/description?CC=DE&NR=102019111402A1&KC=A1&FT=D&ND=3&date=20191128&DB=&locale=en_EP#