Performance Comparison of Kalman Filter and Mean Shift Algorithm for Object Tracking
نویسندگان
چکیده
منابع مشابه
Performance Comparison of Kalman Filter and Mean Shift Algorithm for Object Tracking
Object tracking is one of the important tasks in the field of computer vision. Some of the areas which need Visual object tracking are surveillance, automated video analysis, etc. Mean shift algorithm is one of the popular techniques for this task and is advantageous when compared to some of the other tracking methods. But this method would not be appropriate in the case of large target appeara...
متن کاملMean Shift and Kalman Filter based Human Face Tracking
Real-time human detection and tracking is a vast, challenging and important field of research. It has wide range of applications in human recognition, human computer interaction (HCI), video surveillance etc. The research for biometric authentication of a person has reached far but real-time tracking of human beings has not gained much importance. Keeping continuous track of person will allow i...
متن کاملResearch on Target Tracking Algorithm based on Improved Mean Shift and Kalman Filter
In this paper we discuss about a target tracking algorithm based on Mean Shift and Kalman Filter, which is suitable for high speed moving target tracking. The basic Mean Shift algorithm is described in this paper as well. Although basic Mean Shift algorithm can realize target tracking without arguments or searching all the areas effectively, it has shortcomings which can limit its effectiveness...
متن کاملMean-Shift Tracking Algorithm for Salient Object Detection in videos
Salient object detection is an interesting subject in the field of video tracking and its applications. The main purpose of salient object detection is to estimate the position of the object in images in a continuous manner and reliably against dynamic scenes. When object is moving then its detection is a challenging task in much vision area. Two tasks are performed to detect salient object, in...
متن کاملA General Framework for Multi-Human Tracking using Kalman Filter and Fast Mean Shift Algorithms
The task of reliable detection and tracking of multiple objects becomes highly complex for crowded scenarios. In this paper, a robust framework is presented for multi-Human tracking. The key contribution of the work is to use fast calculation for mean shift algorithm to perform tracking for the cases when Kalman filter fails due to measurement error. Local density maxima in the difference image...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Information Engineering and Electronic Business
سال: 2013
ISSN: 2074-9023,2074-9031
DOI: 10.5815/ijieeb.2013.05.03