Real-time people detection from a top-view ToF camera
Chao Wang, Xiuli Ma, Chang Liao · 2018
The traditional people detection is mainly based on the two-dimensional data acquired from RGB images or videos. While with the help of the Time-of-Flight (TOF) camera, researchers can convert traditional two-dimensional data based on images or videos into pseudo-three-dimensional data containing depth information to achieve more accurate people detection. The research of this paper uses only the depth information and it is an important part of people counting. Based on the preprocessing of depth images, an algorithm based on Connected Component Analysis is proposed according to the characteristics of people in top-view scene. Aiming at the shortcomings of the algorithm in the crowd, the 21Hough Transform(HT) people head detection algorithm combined with depth information and priori conditions is proposed. And thus, we succeed in screening out the non-head objects and achieving real-time, accurate people detection. This study lays a solid foundation for the follow-up people counting.