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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

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Showing 1 to 2 of 2 (0.073 seconds)
1

Mobilní aplikace pro bezpečnost domácnosti / Visual Home Security System for iOS-Based Mobile Devices

Bajaník, Filip January 2018 (has links)
The goal of this diploma thesis is to design and implement a mobile application for home security system on the iOS platform. The application introduces a complex solution allowing the transmission of the audio and video streams between the paired mobile devices using WebRTC. The final module represents universal solution for peer-to-peer audio and video communication. The thesis also deals with the field of computer vision, namely efficient motion detection algorithms. The module for motion detection implements ViBe algorithm using Metal. In case that the motion is detected the application notifies a user with a push notification. Synchronization of application data is implemented using Cloudkit and the data persistance using Realm library.
2

Low-power high-resolution image detection

Merchant, Caleb 09 August 2019 (has links)
Many image processing algorithms exist that can accurately detect humans and other objects such as vehicles and animals. Many of these algorithms require large amounts of processing often requiring hardware acceleration with powerful central processing units (CPUs), graphics processing units (GPUs), field programmable gate arrays (FPGAs), etc. Implementing an algorithm that can detect objects such as humans at longer ranges makes these hardware requirements even more strenuous as the numbers of pixels necessary to detect objects at both close ranges and long ranges is greatly increased. Comparing the performance of different low-power implementations can be used to determine a trade-off between performance and power. An image differencing algorithm is proposed along with selected low-power hardware that is capable of detected humans at ranges of 500 m. Multiple versions of the detection algorithm are implemented on the selected hardware and compared for run-time performance on a low-power system.
object detection
image detection
low-power
long-range
high-resolution
image differencing
frame differencing
morphology
multi-threading
hardware acceleration
ARM
Vivante
NXP
GPU
CPU

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