Deep Spatial Regression Model for Image Crowd Counting

Understand

Computer vision techniques have been used to produce accurate and generic crowd count estimators in recent years.

• Due to severe occlusions, appearance variations, perspective distortions and illumination conditions, crowd counting is a very challenging task.
• To this end, we propose a deep spatial regression model(DSRM) for counting the number of individuals present in a still image with arbitrary perspective and arbitrary resolution.
• Our proposed model is based on Convolutional Neural Network (CNN) and long short term memory (LSTM).