Robust Visual Tracking Based on Adaptive Multi-Feature Fusion Using the Tracking Reliability Criterion
نویسندگان
چکیده
منابع مشابه
Robust Visual Tracking Based on Feature Fusion ?
To drive computational visual tracking toward more robust outputs, we need a more accurate and adaptive feature representation of target. In this paper, we propose a tracking algorithm using new multifeature statistical observation model based on the particle filter framework. Four complementary features are described with histograms and fused in a novel way. We demonstrate how to establish obs...
متن کاملRobust visual tracking using feature selection
Visual tracking has become a very important component in computer vision, but achieving a robust, reliable and real time tracking remains a real challenge. In order to improve the actual state-of-the-art, we choose to study and improve one of the most performing adaptive tracker by detection. We selected Struck [27] for this quality performance and his low computational cost that makes it real ...
متن کاملMulti-model Component-Based Tracking Using Robust Information Fusion
One of the most difficult aspects of visual object tracking is the handling of occlusions and target appearance changes due to variations in illumination and viewing direction. To address these challenges we introduce a novel tracking technique that relies on component-based target representations and on robust fusion to integrate model information across frames. More specifically, we maintain ...
متن کاملA hierarchical feature fusion framework for adaptive visual tracking
a r t i c l e i n f o A Hierarchical Model Fusion (HMF) framework for object tracking in video sequences is presented. The Bayesian tracking equations are extended to account for multiple object models. With these equations as a basis a particle filter algorithm is developed to efficiently cope with the multi-modal distributions emerging from cluttered scenes. The update of each object model ta...
متن کاملRobust video object tracking using particle filter with likelihood based feature fusion and adaptive template updating
A robust algorithm solution is proposed for tracking an object in complex video scenes. In this solution, the bootstrap particle filter (PF) is initialized by an object detector, which models the time-evolving background of the video signal by an adaptive Gaussian mixture. The motion of the object is expressed by a Markov model, which defines the state transition prior. The color and texture fe...
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: Sensors
سال: 2020
ISSN: 1424-8220
DOI: 10.3390/s20247165