Human-object interaction detection based on graph model

Qing Ye; Xiuju Xu

doi:10.1117/12.2671248

28 April 2023 Human-object interaction detection based on graph model

Qing Ye, Xiuju Xu

Proceedings Volume 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022); 126100A (2023) https://doi.org/10.1117/12.2671248
Event: Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 2022, Wuhan, China

Abstract

Human-Object Interaction (HOI) detection is a fundamental task for understanding real-world scenes. In this paper, a graph model-based human-object interaction detection algorithm is proposed, which aims to make full use of the visual-spatial features and semantic information of human-object instances in the image, thereby improving the accuracy of interaction detection. Aiming at the characteristics of visual-spatial features and semantic information, we take the visual features of human and object instance boxes as nodes, and the corresponding spatial features of interaction relations as edges to construct an initial dense graph, and adaptively update the graph through the spatial and semantic information of instances. The V-COCO dataset is used to evaluate the algorithm, and the final accuracy is significantly improved, which proves the effectiveness of the algorithm.

Citation Download Citation

Qing Ye and Xiuju Xu "Human-object interaction detection based on graph model", Proc. SPIE 12610, Third International Conference on Artificial Intelligence and Computer Engineering (ICAICE 2022), 126100A (28 April 2023); https://doi.org/10.1117/12.2671248

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KEYWORDS

Object detection

Semantics

Visualization

Visual process modeling

Detection and tracking algorithms

Education and training

Data modeling

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