People detection is of great importance in video surveillance. Different approaches have been proposed to achieve accurate detection system. The main problem in people detection systems is that it must maintain a balance between the number of false detections and the number of missing people which limits the global detection results. In order to solve this problem and add robustness to detection, we propose a multiplexor and collector model composed of multiple independent detectors. This model is used to keep the true positive detections provided by a number of detectors and reduce the miss rate. In addition, a fusion model is proposed to check the robustness of the cascaded detection system. A pipeline techniques will also be used to avoid the increasing of detection time.
|Title of host publication||Int’l Conference Proceedings of International Conference on Image Processing, Production and Computer Science (ICIPCS'2016)|
|Subtitle of host publication||March 26-27, 2016 London (UK)|
|Editors||Osama Mohamed Mohamed Ahamed, Abhay Saxena|
|Publisher||Universal Researchers in Civil and Architecture Engineering|
|Number of pages||7|
|Publication status||Published - 1 Mar 2016|
- people detection, counting, surveillance systems, image processing, computer vision