A major limitation to most state-of-the-art visual localization methods is their ineptitude make use of ubiquitous signs and directions that are typically intuitive humans. Localization can greatly benefit from a system capable reasoning about variety cues beyond low-level features, such as street signs, store names, building directories, room numbers, etc.In this work, we tackle the problem text detection in wild, an essential step towards achieving text-based mapping. While current employ...

Surgical procedures such as laparoscopic and robotic surgeries are popular since they invasive in nature use miniaturized surgical instruments for small incisions. Tracking of the (graspers, needle drivers) field view from stereoscopic camera during surgery could further help surgeons to remain focussed reduce probability committing any mistakes. is usually preferred computerized video surveillance, traffic monitoring, military surveillance system, vehicle navigation. Despite numerous...

Abstract Background User interfaces play a vital role in the planning and execution of an interventional procedure. The objective this study is to investigate effect using different user for transrectal robot‐assisted MR‐guided prostate biopsy (MRgPBx) augmented reality (AR) environment. Method End‐user studies were conducted by simulating MRgPBx system with end‐ side‐firing modes. information from operator was rendered on HoloLens as output interface. Joystick, mouse/keyboard, holographic...

Recent text detection frameworks require several handcrafted components such as anchor generation, non-maximum suppression (NMS), or multiple processing stages (e.g. label generation) to detect arbitrarily shaped images. In contrast, we propose an end-to-end trainable architecture based on Detection using Transformers (DETR), that outperforms previous state-of-the-art methods in arbitrary-shaped detection.At its core, our proposed method leverages a bounding box loss function accurately...

Prostate biopsy is considered as a definitive way for diagnosing prostate malignancies. Urologists are currently moving towards MR-guided biopsies over conventional transrectal ultrasound-guided cancer detection. Recently, robotic systems have started to emerge an assistance tool urologists perform biopsies. However, these designed specific clinical environment and cannot be adapted modifications or changes applied the setting and/or workflow. This work presents preliminary design of...

In recent years, agencies around the world have invested huge amounts of effort toward digitizing many aspects world’s cultural heritage. Of particular importance is digitization outdoor archaeological sites. spirit valorization this digital information, groups developed virtual or augmented reality (AR) computer applications themed a object. The problem pose tracking in AR addressed. Different positional systems are analyzed, resulting selection monocular camera-based user tracker....

Visual Odometry (VO) can be categorized as being either direct or feature based. When the system is calibrated photometrically, and images are captured at high rates, methods have shown to outperform feature-based ones in terms of accuracy processing time; they also more robust failure feature-deprived environments. On downside, Direct rely on heuristic motion models seed estimation camera between frames; event that these violated (e.g., erratic motion), easily fail. This paper proposes a...

Positional Encoding (PE) plays a vital role in Transformer's ability to capture the order of sequential information, allowing it overcome permutation equivarience property. Recent state-of-the-art Transformer-based scene text recognition methods have leveraged advantages 2D form PE with fixed sinusoidal frequencies, also known as 2SPE, better encode spatial dependencies characters image. These 2SPE-based Transformer frameworks outperformed Recurrent Neural Networks (RNNs) based methods,...

Monocular Odometry systems can be broadly categorized as being either Direct, Indirect, or a hybrid of both. While Indirect process an alternative image representation to compute geometric residuals, Direct methods the pixels directly generate photometric residuals. Both paradigms have distinct but often complementary properties. This paper presents Unified Formulation for Visual Odometry, referred UFVO, with following key contributions: (1) tight coupling (Direct) and (Indirect)...

The fundamental shortcoming underlying monocular-based localizationand mapping solutions (SfM, Visual SLAM) is the fact thatthe obtained maps and motion are solved up to an unknown scale.Yet, literature provides interesting scale estimationusing cues from focus or defocus of a camera. In this paper, wetake advantage offered by image properly initializeVisual SLAM with correct metric scale. We provide experimentsshowing success proposed method discussits limitations.

Visual Odometry (VO) can be categorized as being either direct or feature based. When the system is calibrated photometrically, and images are captured at high rates, methods have shown to outperform feature-based ones in terms of accuracy processing time; they also more robust failure feature-deprived environments. On downside, Direct rely on heuristic motion models seed estimation camera between frames; event that these violated (e.g., erratic motion), easily fail. This paper proposes a...

Road quality assessment is a crucial part in municipalities’ workto maintain their infrastructure, plan upgrades, and manage theirbudgets. Properly maintaining this infrastructure relies heavily onconsistently monitoring its condition deterioration over time.This can be challenge, especially larger towns cities wherethere lot of city property to keep an eye on. We review roadquality methods currently employed, then describeour novel algorithm aimed at identifying distressed road...

Causal discovery between collections of time-series data can help diagnose causes symptoms and hopefully prevent faults before they occur. However, reliable causal be very challenging, especially when the acquisition rate varies (i.e., non-uniform sampling), or in presence missing points (e.g., sparse sampling). To address these issues, we proposed a new system comprised two parts, first part fills with Gaussian Process Regression, second leverages an Echo State Network, which is type...

INTRODUCTION: The advent of da Vinci surgical robot (Intuitive Surgical, California, USA) has allowed complex procedures in urology, gynecology, cardiothoracic, and pediatric to be performed with better clinical outcomes. end effectors these robots exhibits enhanced dexterity improved range motion leading access precise control during the surgery. Understanding design kinematics (imitating instruments' tooltips) would assist replication their a computer-generated environment. This...

Background and Objective Often times, clinicians use a three-dimensional set of medical images to diagnose plan treatments, which typically include visual identification structures such as bones tissues [1]. This can be challenging task anatomical interest contain significant noise, easily blend with neighboring tissues. We propose tackle 2 cases: (a) treatment planning pelvic fractures where small size ring formed by the fused ischium, ilium, pubis attached sacrum contains vital (including...

RGBD Cameras such as the Microsoft Kinect that can quickly provideusable depth maps have become very affordable, and thusvery popular abundant in recent years. Beyond gaming, RGBDcameras numerous applications, including their use affordable3D scanners. These cameras however are limited theirability to capture finer details. We explore of additional3D reconstruction algorithms enhance producedfrom cameras, allowing them more detail.

Convolutional Neural Networks combined with a state of the artstereo-matching method are used to find and estimate 3D positionof vehicles in pairs stereo images. Pixel positions vehiclesare first estimated separately images usinga Network for regression. These coordinatesare then state-of-art stereo-matching todetermine depth, thus location, vehicles. Weshow this paper that cars can be detected accuracyof approximately 90% tolerated radius error 5%,and Mean Absolute Error 5.25m on depth...

The recent success of hybrid methods in monocular odometry has led to many attempts generalize the performance gains SLAM. However, most fall short several respects, with prominent issue being need for two different map representations (local and global maps), each requiring different, computationally expensive, often redundant processes maintain. Moreover, these maps tend drift respect other, resulting contradicting pose scene estimates, leading catastrophic failure. In this paper, we...