Scene graph extraction from images
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...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
Nanyang Technological University
2022
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/156443 |
| _version_ | 1811690375083982848 |
|---|---|
| author | Ng, Felix Zhen Feng |
| author2 | Liu Ziwei |
| author_facet | Liu Ziwei Ng, Felix Zhen Feng |
| author_sort | Ng, Felix Zhen Feng |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T06:02:59Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/156443 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:02:59Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1564432022-04-16T14:09:01Z Scene graph extraction from images Ng, Felix Zhen Feng Liu Ziwei School of Computer Science and Engineering ziwei.liu@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision 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. Bachelor of Engineering (Computer Science) 2022-04-16T14:09:01Z 2022-04-16T14:09:01Z 2022 Final Year Project (FYP) Ng, F. Z. F. (2022). Scene graph extraction from images. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156443 https://hdl.handle.net/10356/156443 en SCSE21-0366 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Ng, Felix Zhen Feng Scene graph extraction from images |
| title | Scene graph extraction from images |
| title_full | Scene graph extraction from images |
| title_fullStr | Scene graph extraction from images |
| title_full_unstemmed | Scene graph extraction from images |
| title_short | Scene graph extraction from images |
| title_sort | scene graph extraction from images |
| topic | Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision |
| url | https://hdl.handle.net/10356/156443 |
| work_keys_str_mv | AT ngfelixzhenfeng scenegraphextractionfromimages |