Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156443
Title: Scene graph extraction from images
Authors: Ng, Felix Zhen Feng
Keywords: Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Ng, F. Z. F. (2022). Scene graph extraction from images. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156443
Project: SCSE21-0366
Abstract: An image contains a lot of information, and that information can be used in high-level complex systems for operations such as Computer Vision tasks. Most Computer Vision tasks, such as Image Classification and Object Detection, only require outputting an image-level prediction or the localization of objects in the image. However, it is still not sufficient for a comprehensive interpretation of all the information in an image. To deliver all the information within an image, a generated Scene Graph can be used. A Scene Graph is a structured representation of a scene that clearly express the objects and their attributes in the form of nodes, and relationships between objects in the form of edges, so that a graph structure can be built. This project aims to understand Scene Graph Generation, explore several classic methodologies by evaluating and comparing the correctness of predicted scene graph models, and find the key factors that affect the correctness of scene graphs. Many insights had been discovered in this project, for example, prior knowledge (which can be interpreted as common sense), can greatly affect the performance of Scene Graph Generation. Additionally, it was observed that models with a better backbone generated a more accurate Scene Graph. Beyond the exploration of methodologies, a software was developed to process photos captured from a connected webcam into a Scene Graph.
URI: https://hdl.handle.net/10356/156443
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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