Visual tracking is very challenging due to the existence of several sources of variations, such as partial occlusion, deformation, scale variation, rotation, and background clutter. A model-free tracking method based on fusing accelerated features using fast explicit diffusion in nonlinear scale spaces (AKAZE) and KLT features is presented. First, matching-keypoints are generated by finding cor...

Small-scale unmanned aerial vehicles are being deployed in urban areas for missions such as ground target tracking, crime scene monitoring, and traffic management. Aerial cluttered environments required to have robust autonomous navigation with both tracking obstacle avoidance capabilities. To this end, work presents a simple-to-design but effective steerable sensor platform its implementation ...

multiple people detection and tracking is a challenging task in real-world crowded scenes. in this paper, we have presented an online multiple people tracking-by-detection approach with a single camera. we have detected objects with deformable part models and a visual background extractor. in the tracking phase we have used a combination of support vector machine (svm) person-specific classifie...

Formant tracking is investigated in this study by using trackers based on dynamic programming (DP) and deep neural nets (DNNs). Using the DP approach, six formant estimation methods were first compared. The include linear prediction (LP) algorithms, weighted LP algorithms recently developed quasi-closed phase forward-backward (QCP-FB) method. QCP-FB gave best performance comparison. Therefore, ...

Vehicle detection and tracking with unmanned aerial vehicles (UAVs) find increasingly widespread applications in both military and civilian domains. In this paper, a method for vision-based multiple vehicle detection by using the proposed self –learning tracking and detection (SLTD) method has been proposed. The method used Features from Accelerated Segment Test (FAST) and Histograms of Oriente...

This article presents a low-complexity and high-accuracy algorithm using message-passing approach to reduce the computational load of the traditional tracking algorithm for location estimation. In the proposed tracking scheme, a state space model for the location-estimation problem can be divided into many mutual-interaction local constraints based on the inherent message-passing features of fa...

Effective target detection and tracking has always been a research hotspot in the field of radar, multi-target is focus radar at present. In order to effectively deal with issue outlier removal track initiation determination process tracking, this paper proposes an improved backward smoothing method based on label iterative processing. This corrects loophole original method, which can cause est...

‎in this paper a nonlinear backward parabolic problem in one‎ ‎dimensional space is considered‎. ‎using a suitable iterative‎ ‎algorithm‎, ‎the problem is converted to a linear backward parabolic‎ ‎problem‎. ‎for the corresponding problem‎, ‎the backward finite‎ ‎differences method with suitable grid size is applied‎. ‎it is shown‎ ‎that if the coefficients satisfy some special conditions‎, ‎th...

In this work, we focus on the model-mismatch problem for model-based subspace channel tracking in correlated underwater acoustic channel. A model based channel's correlation can be used as state-space Kalman filter to improve compared that without a model. Even though data support assumption is slow-varying and uncorrelated some degree, performance further, not ignore because most models encoun...

This paper presents an adaptive multigrid approach, combining adaptive local grid refinement and multigrid methods, in conjunction with the Lagrangian–Eulerian finite element method to simulate contaminant transport in the 3D subsurface. Adaptive local grid refinement can improve solution accuracy without sacrificing computational efficiency because computer efforts are focused on the rough reg...