Human recognition for surveillance systems using bounding box

Abstract

In all computer vision system, the important step is to separate moving object from background and thus detecting all the objects from video images. The main aim of this paper is to design a bounding box concept for the human detection and tracking system in the presence of crowd. The images are captured by using monocular cameras. The bounding box around each object can track the moving objects in each frame and it can be used to detect crowd and the estimation of crowd. This paper gives the implementation results of bounding box for detecting objects and its tracking.

Estimation for Motion in Tracking and Detection Objects with Kalman Filter

“…In the case of tracking an object in motion, the Kalman filter allows us to estimate the states of motion of the object. Many authors have studied the Kalman filter in object tracking [1,8,9], the differences of the present work and the earlier works are the type and the method of objects tracking.…”

“…From the works that are studied in the literature [1,4,5], we chose the Kalman filter for estimating the tracking parameters. Figure 4 shows the Kalman filter cycle [8][9][10]. Generally the estimation of the tracking parameters with a Kalman filter is a process requires the following steps: itemize.…”

Tracking Human Motion Based on Bounding Box Concept

“…In 2014, [1] presented a paper on motion human detection based on background Subtraction using bounding box concept which proposes a new method to detect moving object based on background subtraction. Moving object can obtain using dynamic threshold method and background updating model and detect the object by using bounding box.…”