MBR-MDA: Multi-person Behavior Recognition Method Based on Multi Descriptors Aggregations
Yang Cathy Luo, Lin Rongheng · Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering · 2023
Multi-person behavior recognition is an important task in intelligent video surveillance.In this paper, we propose a multi-person behavior recognition method based on multi descriptors aggregations (MBR-MDA) for real-time surveillance scenarios.Our method employs multi-object tracking to obtain consecutive frames of each person, and uses a 2D convolutional network with temporal shift module (TSM) for behavior recognition.To address the limitation of 2D convolutional network in capturing global temporal features, we introduce a plugand-play module called MDA that can be integrated into the 2D convolutional network.By applying data augmentation and embedding the MDA3D module, our method achieves a 4.8% improvement over TSM baseline on the HMDB51 dataset, with only a minimal speed loss of 0.3ms.We evaluate our method on several public datasets and demonstrate that embedding MDA into other methods can also enhance their performance.