Disparity map generation based on trapezoidal camera architecture for multiview video

Visual content acquisition is a strategic functional block of any visual system. Despite its wide possibilities, the arrangement of cameras for the acquisition of good quality visual content for use in multi-view video remains a huge challenge. This paper presents the mathematical description of trapezoidal camera architecture and relationships which facilitate the determination of camera position for visual content acquisition in multi-view video, and depth map generation. The strong point of Trapezoidal Camera Architecture is that it allows for adaptive camera topology by which points within the scene, especially the occluded ones can be optically and geometrically viewed from several different viewpoints either on the edge of the trapezoid or inside it. The concept of maximum independent set, trapezoid characteristics, and the fact that the positions of cameras (with the exception of few) differ in their vertical coordinate description could very well be used to address the issue of occlusion which continues to be a major problem in computer vision with regards to the generation of depth map

Improved Contrast Sensitivity DVS and its Application to Event-Driven Stereo Vision

This paper presents a new DVS sensor with one order of magnitude improved contrast sensitivity over previous reported DVSs. This sensor has been applied to a bio-inspired event-based binocular system that performs 3D event-driven reconstruction of a scene. Events from two DVS sensors are matched by using precise timing information of their ocurrence. To improve matching reliability, satisfaction of epipolar geometry constraint is required, and simultaneously available information on the orientation is used as an additional matching constraint.Ministerio de Economía y Competitividad PRI-PIMCHI-2011-0768Ministerio de Economía y Competitividad TEC2009-10639-C04-01Junta de Andalucía TIC-609

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Vide-omics : a genomics-inspired paradigm for video analysis

With the development of applications associated to ego-vision systems, smart-phones, and autonomous cars, automated analysis of videos generated by freely moving cameras has become a major challenge for the computer vision community. Current techniques are still not suitable to deal with real-life situations due to, in particular, wide scene variability and the large range of camera motions. Whereas most approaches attempt to control those parameters, this paper introduces a novel video analysis paradigm, 'vide-omics', inspired by the principles of genomics where variability is the expected norm. Validation of this new concept is performed by designing an implementation addressing foreground extraction from videos captured by freely moving cameras. Evaluation on a set of standard videos demonstrates both robust performance that is largely independent from camera motion and scene, and state-of-the-art results in the most challenging video. Those experiments underline not only the validity of the 'vide-omics' paradigm, but also its potential

A Small-Scale 3D Imaging Platform for Algorithm Performance Evaluation

In recent years, world events have expedited the need for the design and application of rapidly deployable airborne surveillance systems in urban environments. Fast and effective use of the surveillance images requires accurate modeling of the terrain being surveyed. The process of accurately modeling buildings, landmarks, or other items of interest on the surface of the earth, within a short lead time, has proven to be a challenging task. One approach of high importance for countering this challenge and accurately reconstructing 3D objects is through the employment of airborne 3D image acquisition platforms. While developments in this arena have significantly risen, there remains a wide gap in the verification of accuracy between the acquired data and the actual ground-truth data. In addition, the time and cost of verifying the accuracy of the acquired data on airborne imaging platforms has also increased. This thesis investigation proposes to design and test a small-scale 3D imaging platform to aid in the verification of current image acquisition, registration and processing algorithms at a lower cost in a controlled lab environment. A rich data set of images will be acquired and the use of such data will be explored

Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page

Система визначення глибини зображення

Робота публікується згідно наказу Ректора НАУ від 27.05.2021 р. №311/од "Про розміщення кваліфікаційних робіт здобувачів вищої освіти в репозиторії університету" . Керівник роботи: к. т. н., ст. викл. кафедри авіаційних комп’ютерно-інтегрованих комплексів, Василенко Микола ПавловичIn today's world, there is often a question about creating a model to solve a certain problem in such a way that it performs its intended task properly and does not have a large cost. This is what almost every developer of the project wants at the production stage. Thus, the work consists in improving and acquiring better accuracy of the image depth detection system. For this, was modified and improved, namely, the main design of the model was changed and the quality of the image was improved, thanks to various methods of image filtering. Unlike the previous model, this project investigates the effect and quality of the 3D scene construction in the image, not the streaming video, under different weather conditions and at different observation points, which makes it possible to feel in more detail the impact of various phenomena on the model itself during operation and improve accuracy due to considering a single pair of images rather than a stream of large numbers at a specific frequency. The design consists of two cameras, which were selected from the principle of price-quality, and a box to fix and protect the model itself, thus forming protection from the environment in various conditions of use. The design is connected to a computer that performs the software part, which consists in creating a stereo pair – artificial adjustment of cameras, image analysis at the initial stage and after filtering, which as a result gives an opportunity to see the difference in the accuracy of constructing a 3D image, which can be used for various goals, for example to find out the size or distance to the target object.У сучасному світі часто постає питання про створення моделі вирішення певної задачі таким чином, щоб вона якісно виконувала поставлене завдання і не мала великих витрат. Це те, чого хоче практично кожен розробник проекту на етапі виробництва. Таким чином, робота полягає в удосконаленні та підвищенні точності системи визначення глибини зображення. Для цього виготовлена модель була модифікована та вдосконалена, а саме змінено основну конструкцію моделі та покращено якість зображення, завдяки різним методам фільтрації зображення. На відміну від попередньої моделі, цей проект досліджує ефект і якість побудови 3D-сцени в зображенні, а не в потоковому відео, за різних погодних умов і в різних точках спостереження, що дає можливість більш детально відчути вплив різних явищ. на самій моделі під час роботи та підвищити точність за рахунок розгляду однієї пари зображень, а не потоку великих чисел із певною частотою. Конструкція складається з двох камер, підібраних за принципом ціна-якість, і коробки для кріплення і захисту самої моделі, формуючи таким чином захист від зовнішнього середовища в різних умовах використання. Конструкція підключена до комп’ютера, який виконує програмну частину, яка полягає у створенні стереопари – штучне налаштування камер, аналіз зображення на початковому етапі та після фільтрації, що в результаті дає можливість побачити різницю в точності. побудови тривимірного зображення, яке можна використовувати для різних цілей, наприклад, щоб дізнатися розмір або відстань до цільового об'єкта

Application of Freeway Video Surveillance for Accident Investigation

This report presents information on Research Project Number Z820 (UNL Ref. No. 26-1118- 0057-001) titled “Application of Freeway Video Surveillance for Accident Investigation.” Traffic accident investigation requires detailed documentation of the accident scene, vehicles, and persons involved in the collision. To adequately document an accident scene, investigating officers accurately record various measurements (e.g., skid marks, dimensions of different highway geometric elements, etc.). Typically, a measuring tape and/or a total station (theodolite) are used to obtain the needed measurements. Advances in digital imaging and computer technology make it possible to develop cost-effective traffic accident investigation system alternatives that provide sufficient accuracy, significant time savings, and reduced costs. Utilizing stereo machine vision technology an accident investigation system, called the UNL Traffic Accident Investigation Tool (TAIT) consisting of two digital cameras and measurementextraction software tool were developed in this project. A mock traffic accident was investigated using TAIT. Measurements provided by TAIT were compared to true values obtained by using a measuring tape. The accuracy of TAIT satisfied requirements of traffic accident investigation agencies. In addition, equipment costs as well as investigation time were reduced compared to the typical accident data collection methods. The UNL TAIT is a prototype and requires further development before it can be integrated into the day-today operations of agencies investigating traffic accidents