A Real-time Moving Isolate Detection Based On Dynamic Background

In the study of computer vision,moving object detection is one of the most important part And detecting moving isolate under dynamic background quickly and precisely is also of paramount importance.With the development of economy and advent of living standards,as a field based on various interdisc:iplinary,the theory research and practical application of the computer vision has made great progress,And at the same time,the research in the field of computer vision is also promoting the growth of artificial intelligence.This paper mainly discussed the algorithm proposed and its two application methods,that are the separated tissue detection based on endoscope and the abandoned object detection based on smart tachograph videos.The moving isolate detection system proposed in this paper treated the videos recorded by endoscope and smart tachograph as experimental data.And compared to the traditional system,the system in this paper is more complex and challenging.The moving isolate detection system could be divided into two parts,one is object tracking,another is abandoned object detectiob.In the part of object tracking,both the particle filter and Harris-SIFT features are used to achieve moving object tracking.First of all,the particle filter is applied to predict the candidate area in the current frame.Furthermore,the Harris-SIFT feature descriptor,extracted from the candidate area,is constructed.Finally,the vector is updated according to the matching between object model and the feature points in the candidate area during the tracking process.When detected the moving isolate,compared to the other isolate detection methods,the proposed method is different in both detection environment and movement of the target vehicle.At the beginning with,we use ViBE algorithm to generate the background model according to the target obtained from object tracking.Then,the background subtraction method is used to detect the moving foreground region.The frame difference method is then applied between the foreground and the newest frame obtained.Finally,we apply the Otsu algorithm to detect the frames during the duration when the object is abandoned.In order to verify the feasibility of this algorithm directly,Firstly,the results of the separated tissue is displayed.And then,both the detection results in ideal condition and in practical condition is presented,the results we have gotten from the experiments shows the proposed algorithm is accurate an robust under different and complex conditions.