Estimating Context Aware Human-Objects Interaction using Deep Learning-Based Object Recognition Architectures
| Autor: | San Martín Fernández, Iván |
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| Přispěvatelé: | Garcia-Rodriguez, Jose, Oprea, Sergiu, Universidad de Alicante. Departamento de Tecnología Informática y Computación |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | RUA. Repositorio Institucional de la Universidad de Alicante Universidad de Alicante (UA) |
| Popis: | In this work, we propose an architecture for predicting plausible person-object interactions based on image visible objects and room recognition. First of all, the system detects objects in the video using a popular framework named ”YOLO” (You Only Look Once) and associates each object with their possible interactions. Then, making use of a convolutional neural network, our algorithm recognizes which is the room that appears in the image and filters possible context aware human-object interactions. The main purpose of this project is helping people with memory failures to do perform daily activities. Many people have problems carrying out actions that can be natural for the rest. With the aim to assist them, we are interested in the development of methods which allow remembering them the actions they may have forgotten. |
| Databáze: | OpenAIRE |
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