Background subtraction based object extraction for Time-of-Flight sensor
Shung Han Cho, Kwanghyuk Bae, Kyu-Min Kyung, Seongyeong Jeong, Tae-Chan Kim · 2013
This paper presents a moving object extraction method using background subtraction techniques for Time-of-Flight sensor. Time-of-Flight sensor obtains two different types of data at the same time. One is depth data representing the distance to objects and another is intensity data representing the confidence level of depth data. After each reference background model is constructed for depth and intensity data, each foreground object map is obtained for depth and intensity data by comparing to its reference background model. Final foreground objects are extracted by combining two foreground object maps to remove noise data. The simulation results with MESA SR4000 show that the proposed method extracts moving objects accurately.