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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 | Schools: | School of Computer Science and Engineering | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Student Reports (FYP/IA/PA/PI) |
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File | Description | Size | Format | |
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U1922582F_FYP_Report.pdf Restricted Access | 8.02 MB | Adobe PDF | View/Open |
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