Photometric Calibration for Stereo Camera with Gamma-like Response Function in Direct Visual Odometry

Direct visual odometry algorithms assume that every frame from the camera has the same photometric characteristics. However, the cameras with auto exposure are widely used outdoors as the environment often changes. The vignetting also affects the pixel’s brightness on different frames, even if the exposure time is fixed. We propose an online vignetting correction and exposure time estimation method for stereo direct visual odometry algorithms. Our method works on a camera that has a gamma-like response function. The inverse vignetting function and exposure time ratio between neighboring frames are estimated. Stereo matching is used to select correspondences between the left image and right image in the same frame at the initialization step. Feature points are used to pick the correspondences between different frames. Our method provides static correction results during the experiments on datasets and a stereo camera.

Microsurgical Resection of a Parasellar Meningioma Invading the Cavernous Sinus, Bone, and Optic Canal: 2-Dimensional Operative Video

Parasellar meningiomas, regardless of the initial origin, frequently involve the optic canal and cavernous sinus, leading to visual loss and ocular movement dysfunction.1 Hyperostotic bony invasion to the surrounding skull base is common.2 Visual acuity prognosis can be improved by surgical resection through different technical maneuvers, including opening the optic canal and the preservation of the visual apparatus vascular supply by developing the intra-arachnoidal dissection planes.1,3,4 To achieve radical dissection and reduce recurrences, the extradural invaded bone is thoroughly resected. Likewise, the soft and nonadherent invasive tumor around the cavernous carotid can be extensively removed.1,3,4 New or worsening of the ophthalmoplegia is frequent after cavernous sinus exploration and tumor resection. However, it is usually temporary and improves progressively in 80% of patients.1,3,4 Safely approaching these lesions requires extensive anatomic knowledge through cadaveric dissection and training, allowing us to achieve tumor control, preserve or improve visual function, and avoid or delay irradiation therapy.1,3,4 Pituitary function preservation is also possible in many patients through surgery, which is at higher risk with irradiation. We demonstrate the technical maneuvers through a case of a 49-yr-old woman who presented with a parasellar meningioma involving the cavernous sinus, both optic canals, and extensive bony invasion. The patient consented to the surgery and publication of her images. Image at 1:14 and middle and right image at 1:31 reprinted with permission from Al-Mefty O, Operative Atlas of Meningiomas. Vol 1, ©LWW, 1998. Left image at 1:31 reprinted from Arnautovic et al,5 by permission from JNSPG.

A Fast Stereo Matching Network with Multi-Cross Attention

Stereo matching networks based on deep learning are widely developed and can obtain excellent disparity estimation. We present a new end-to-end fast deep learning stereo matching network in this work that aims to determine the corresponding disparity from two stereo image pairs. We extract the characteristics of the low-resolution feature images using the stacked hourglass structure feature extractor and build a multi-level detailed cost volume. We also use the edge of the left image to guide disparity optimization and sub-sample with the low-resolution data, ensuring excellent accuracy and speed at the same time. Furthermore, we design a multi-cross attention model for binocular stereo matching to improve the matching accuracy and achieve end-to-end disparity regression effectively. We evaluate our network on Scene Flow, KITTI2012, and KITTI2015 datasets, and the experimental results show that the speed and accuracy of our method are excellent.

Digital watermarking of 3D disparity map based images for transaction tracking

In this thesis, the basics of disparity map and watermarking are reviewed extensively. In order to embed binary information into images, a 3D image watermarking system was proposed. This embedded information was to survive the 3D Image rendering process of Disparity maps, to help identify malicious user who would distribute the watermarked image through an unauthorized system. The proposed system adopted the concept of hidden pixel and introduced an algorithm that identifies all known hidden pixels within the image. This information is combined with the Disparity map to generate a hidden pixel disparity map (HPDM); using the information in the HPDM a decision matrix is generated. This decision matrix is used to guide the watermark embedding process to ensure that information embedded in the Left Image can survive the 3D rendering process. Using the decision matrix, the watermark detector is capable of extracting the image from either the left or right image with no effect on the overall bit rate. This achievement is due to two original additions to the detection process: (1) Reverse rendering and (2) Cyclical Redundancy check. The proposed reverse rendering process expands the decision matrix into a reduced disparity map. This reduced disparity map is used to reverse the right image into a reduced left image. The identification of the image (left or right) is achieved through the use of a CRC check, which is also capable of detecting any errors in the extracted message, thus reducing the number of misidentification. The proposed system was implemented and tested using MATLAB. The bit efficiency of the proposed system varied between 38% and 88%. This variance is caused by the complexity of the depth scene as well as the cost function used in the depth estimation process. The watermark embedding system proposed had a PSNR of 45 dB (when no mark was embedded); this value is primarily attributed to some of the quantization that occurs during the DCT transform. However, a PSNR of 33dB is attained when the watermark was added at full strength.

Digital watermarking of 3D disparity map based images for transaction tracking

In this thesis, the basics of disparity map and watermarking are reviewed extensively. In order to embed binary information into images, a 3D image watermarking system was proposed. This embedded information was to survive the 3D Image rendering process of Disparity maps, to help identify malicious user who would distribute the watermarked image through an unauthorized system. The proposed system adopted the concept of hidden pixel and introduced an algorithm that identifies all known hidden pixels within the image. This information is combined with the Disparity map to generate a hidden pixel disparity map (HPDM); using the information in the HPDM a decision matrix is generated. This decision matrix is used to guide the watermark embedding process to ensure that information embedded in the Left Image can survive the 3D rendering process. Using the decision matrix, the watermark detector is capable of extracting the image from either the left or right image with no effect on the overall bit rate. This achievement is due to two original additions to the detection process: (1) Reverse rendering and (2) Cyclical Redundancy check. The proposed reverse rendering process expands the decision matrix into a reduced disparity map. This reduced disparity map is used to reverse the right image into a reduced left image. The identification of the image (left or right) is achieved through the use of a CRC check, which is also capable of detecting any errors in the extracted message, thus reducing the number of misidentification. The proposed system was implemented and tested using MATLAB. The bit efficiency of the proposed system varied between 38% and 88%. This variance is caused by the complexity of the depth scene as well as the cost function used in the depth estimation process. The watermark embedding system proposed had a PSNR of 45 dB (when no mark was embedded); this value is primarily attributed to some of the quantization that occurs during the DCT transform. However, a PSNR of 33dB is attained when the watermark was added at full strength.

Bipolar membrane polarization behavior with systematically varied interfacial areas in the junction region

Left image is the relationship for the overpotential for water dissociation as a function of bipolar junction electric field whereas the right image presents micrographs and the procedure to make bipolar membranes with micropatterned interfaces.

Self-Guided Stereo Correspondence Estimation Algorithm

This paper introduces an innovative algorithm, “Self-guided Stereo Correspondence” (SGSC), that is directed by photometric properties of the candidate pixels. As the photometric properties of reference image (left image) pixel and its neighbor’s pixel are similar in most cases, so the upcoming corresponding pixel exists in the surrounding of the previous matching pixel. Searching performance is greatly improved by utilizing this photometric property of the candidate pixels. The searching performance is further improved by applying the pioneering threshold technique. These two key techniques sufficiently reduced the computational cost with no degradation of accuracy. The achievements of the proposed method are testified on Middlebury standard Stereo Datasets of 2003 and 2006 and the Middlebury latest Optical Flow Dataset. Finally, the proposed method is compared with present state-of-the-art methods and our SGSC outdoes the latest methods in terms of speed, visualization of hidden ground truth, 3D reconstruction and accuracy.

A Taillight Matching and Pairing Algorithm for Stereo-Vision-Based Nighttime Vehicle-to-Vehicle Positioning

The stereo vision system has several potential benefits for delivering advanced autonomous vehicles compared to other existing technologies, such as vehicle-to-vehicle (V2V) positioning. This paper explores a stereo-vision-based nighttime V2V positioning process by detecting vehicle taillights. To address the crucial problems when applying this process to urban traffic, we propose a three-fold contribution as follows. The first contribution is a detection method that aims to label and determine the pixel coordinates of every taillight region from the images. Second, a stereo matching method derived from a gradient boosted tree is proposed to determine which taillight in the left image a taillight in the right image corresponds to. Third, we offer a neural-network-based method to pair every two taillights that belong to the same vehicle. The experiment on the four-lane traffic road was conducted, and the results were used to quantitatively evaluate the performance of each proposed method in real situations.

An Augmented Reality Head-Up Display System with a Wide-View Eyebox

This study proposes to apply the combination of two 90-degree prisms and a holographic optical element to an image-dividing element, divide an image into three through the virtual image projection system, and accurately project the images to 160 cm behind the windshield. In order to distinguish the left image, middle image, and right image at the horizontal direction, the 90-degree prism is first utilized for horizontally deflecting the light, a holographic optical element is then used for presenting the vertical deflection of the image, and finally, the images are horizontally arranged as a real image on the diffuser. An image-dividing element is eventually integrated to the virtual image projection system. Then, the divided images are made as a virtual image which is projected to 160 cm behind the windshield to combine with the street scene. The horizontal angle of view of an eyebox is increased from 2.51° to 7.22°, and the size of the eyebox is 31.68 cm × 12.48 cm, allowing a wide-view laser-based head-up display with the large-angle beam-splitting function being successfully designed. It would not affect the field of view on the road, and this system could reduce the space and be arranged easily in a vehicle. Therefore, this proposed system is suitable for the aftermarket.

Teenage boy with bullous rash

­A 14-year-old boy with recent antibiotic treatment for tonsillitis, presented to the emergency department with 1-week history of worsening rash and haemorrhagic bullae involving the bilateral legs, trunk and hands (figures 1 and 2). Laboratory results were significant for proteinuria (2+protein) and haematuria (1+, 5–10 red blood cells/high power field); 24 hours urinary protein and renal function were within normal limits. The patient had an inconclusive skin biopsy.Figure 1Left and right images show palpable purpura with some overlying bullae and vesiculation coalescing into plaques on both lower extremities.Figure 2Left image shows rash on abdominal wall and right image shows coalesced haemorrhagic bullae on hands.QuestionsWhat is the most probable diagnosis?Bullous Ig A vasculitisMeningococcemiaBullous impetigoEosinophilic granulomatosis with polyangiitisCryoglobulinemiaWhat is the best test which will establish the diagnosis in this patient?Renal ultrasoundRenal biopsyAbdominal ultrasoundCreatinine clearanceWhat is first line of treatment in this patient?AntibioticsSteroidsSurgical debridementMultispecialty consultationImmunosuppressants such as azothioprineWhat other systems can this condition affect besides the skin?LungsKidneysSpleenNervous systemA, B and DAnswers can be found on page 02.