A novel multi-stream method for violent interaction detection using deep learning

A novel multi-stream method for violent interaction detection using deep learning

Blog Article

Violent interaction detection is a hot topic in computer vision.However, the recent research works on violent interaction detection mainly focus on the traditional hand-craft features, and does not make full use of the research results of deep learning in computer vision.In this paper, we propose a new robust violent interaction detection framework based on multi-stream deep learning in surveillance scene.

The proposed approach enhances the recognition performance of violent action in video by fusing three different hbl5266ca streams: attention-based spatial RGB stream, temporal stream, and local spatial stream.The attention-based spatial RGB stream learns the spatial attention regions of persons that have high probability to be action region through soft-attention mechanism.The temporal stream employs optical flow as input to extract temporal features.

The local spatial stream learns spatial local features using block images as input.Experimental results demonstrate the 15-eg1053cl effectiveness and reliability of the proposed method on three violent interactive datasets: hockey fights, movies, violent interaction.We also verify the proposed method on our own elevator surveillance video dataset and the performance of the proposed method is satisfied.