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The topic of this master's thesis is devoted to design and realization of autonomous camera system of the selected object with possibility of remote access. The content of the theoretical part is description of components of the camera system and close analysis of the used software, including the selection of suitable components. The practical part is approaching to the initial installation of the system and verification of the functionality of individual components based on simple commands. The next step is developing an mobile application comunicattting with the camera system based on low data flow.

The purpose of this project was to research the virtual camera systems used in current generation third person action games and to see what could be improved upon. To do this, different camera shots were categorized into camera archetypes, which also include post process and lens effects used. Information about the games was acquired by either looking through the game’s settings or by observing gameplay. Finally the results were compared to each other as well as the film industry and several improvements regarding usage of different features and camera shots were suggested.

abstract: Minimally invasive surgery is a surgical technique that is known for its reduced patient recovery time. It is a surgical procedure done by using long reached tools and an endoscopic camera to operate on the body though small incisions made near the point of operation while viewing the live camera feed on a nearby display screen. Multiple camera views are used in various industries such as surveillance and professional gaming to allow users a spatial awareness advantage as to what is happening in the 3D space that is presented to them on 2D displays. The concept has not effectively broken into the medical industry yet. This thesis tests a multi-view camera system in which three cameras are inserted into a laparoscopic surgical training box along with two surgical instruments, to determine the system impact on spatial cognition, perceived cognitive workload, and the overall time needed to complete the task, compared to one camera viewing the traditional set up. The task is a non-medical task and is one of five typically used to train surgeons’ motor skills when initially learning minimally invasive surgical procedures. The task is a peg transfer and will be conducted by 30 people who are randomly assigned to one of two conditions; one display and three displays. The results indicated that when three displays were present the overall time initially using them to complete a task was slower; the task was perceived to be completed more easily and with less strain; and participants had a slightly higher performance rate. / Dissertation/Thesis / Masters Thesis Human Systems Engineering 2019

To make three dimensional measurements using a stereo camera system, the intrinsic and extrinsic calibration of the system should be obtained. Furthermore, to allow zooming, intrinsic parameters should be re-estimated using only scene constraints. In this study both manual and autocalibration algorithms are implemented and tested. The implemented manual calibration system is used to calculate the parameters of the calibration with the help of a planar calibration object. The method is tested on different internal calibration settings and results of 3D measurements using the obtained calibration is presented. Two autocalibration methods have been implemented. The first one requires a general motion while the second method requires a pure rotation of the cameras. The autocalibration methods require point matches between images. To achieve a fully automated process, robust algorithms for point matching have been implemented. For the case of general motion the fundamental matrix relation is used in the matching algorithm. When there is only rotation between views, the homography relation is used. The results of variations on the autocalibration methods are also presented. The result of the manual calibration has been found to be very reliable. The results of the first autocalibration method are not accurate enough but it has been shown that the calibration from rotating cameras performs precise enough if rotation between images is sufficiently large.

This diploma thesis deals with the research of fast processes. It delineates technique the process is captured by with following interpretation of the results received. Fast processes are captured using high speed video camera system Olympus i-SPEED 2. The actual object of measuring and examination was an air pistol and its initial velocity.

This diploma thesis introduces Olympus i-SPEED 2 high speed video camera and its use in the testing of rubber parts. The results gained will be applied to tyre tread development. Two mutually connected high speed cameras were used to record the testing process. Final recordings were put together in order to create panoramic photos.

This thesis deals with the evaluation of manufacturing gas valves on the automatic line and the design of CCTV systems to detect errors at assembly in Honeywell Czech Republic Ltd. The aim of this thesis is mutual comparison of the respective proposed options of the camera system, their optimal selection, and the evaluation of detected errors of the line by using Pareto Charts. An integral part of this work is a brief description of the automatic line for gas valves and the history of Honeywell Company.

This thesis deals with realization of modular camera system. Introductory part is focused on market research and concept of the system. Next part is dedicated to the choice of components for realization of the system. Practical part deals firstly with design of printed circuit board for supporting control unit which will be controlling peripherals like motion sensor, IR illuminator, eventually magnetic door contact and also focuses on software creation for main and supporting control unit.

Indiana University-Purdue University Indianapolis (IUPUI) / Analyzing behaviors of objects on the road is a complex task that requires data from various sensors and their fusion to recreate the movement of objects with a high degree of accuracy. A data collection and processing system are thus needed to track the objects accurately in order to make an accurate and clear map of the trajectories of objects relative to various coordinate frame(s) of interest in the map. Detection and tracking moving objects (DATMO) and Simultaneous localization and mapping (SLAM) are the tasks that needs to be achieved in conjunction to create a clear map of the road comprising of the moving and static objects. These computational problems are commonly solved and used to aid scenario reconstruction for the objects of interest. The tracking of objects can be done in various ways, utilizing sensors such as monocular or stereo cameras, Light Detection and Ranging (LIDAR) sensors as well as Inertial Navigation systems (INS) systems. One relatively common method for solving DATMO and SLAM involves utilizing a 3D LIDAR with multiple monocular cameras in conjunction with an inertial measurement unit (IMU) allows for redundancies to maintain object classification and tracking with the help of sensor fusion in cases when sensor specific traditional algorithms prove to be ineffectual when either sensor falls short due to their limitations. The usage of the IMU and sensor fusion methods relatively eliminates the need for having an expensive INS rig. Fusion of these sensors allows for more effectual tracking to utilize the maximum potential of each sensor while allowing for methods to increase perceptional accuracy. The focus of this thesis will be the dock-less e-scooter and the primary goal will be to track its movements effectively and accurately with respect to cars on the road and the world. Since it is relatively more common to observe a car on the road than e-scooters, we propose a data collection system that can be built on top of an e-scooter and an offline processing pipeline that can be used to collect data in order to understand the behaviors of the e-scooters themselves. In this thesis, we plan to explore a data collection system involving a 3D LIDAR sensor and multiple monocular cameras and an IMU on an e-scooter as well as an offline method for processing the data to generate data to aid scenario reconstruction.