Crowd Counting_2020

Crowd Counting Evaluation

• We focus on crowd counting on drone-captured scenes. In particular, given an input frame in bird-view, we require a counting method to estimate the number of people and density map in an image accurately.
• For this task, the performance is evaluated by both MAE and MSE scores, same as in [1]. Notably, the MAE score is used as the primary metric for ranking methods. The metrics are described in the following table.

MEASURE	PERFECT	DESCRIPTION
MAE	0	Mean absolute error between the predicted number of people and ground-truth in evaluation
MSE	0	Mean squared error between the predicted number of people and ground-truth in evaluation

The evaluation code for crowd counting is available on the VisDrone github.

References:

[1] Wen, L., Du, D., Zhu, P., Hu, Q., Wang, Q., Bo, L., & Lyu, S. (2019). Drone-based Joint Density Map Estimation, Localization and Tracking with Space-Time Multi-Scale Attention Network.arXiv preprint arXiv:1912.01811.