In this paper, we proposed an object tracking method for video stream based on conventional particle filter. Feature vectors are extracted from coefficient matrices of Discrete Cosine Transform (DCT). The feature, as experiment showed, is very robust to occlusion and rotation and it is not sensitive to scale changes. The proposed method is efficient enough to be used in a real-time application....

Abstract- Kernel trick and projection to tangent spaces are two choices for linearizing the data points lying on Riemannian manifolds. These approaches are used to provide the prerequisites for applying standard machine learning methods on Riemannian manifolds. Classical kernels implicitly project data to high dimensional feature space without considering the intrinsic geometry of data points. ...

In image processing, the tracking of visible objects through time is a very common task. This task normally requires the definition of the object boundaries in order to describe its motion. However, that approach not always gives sufficient information about the position of specific points located on the surface of the object, especially in case the shape of the object also changes. Using addit...

Inter-frame Coding plays significant role for video Compression and Computer Vision. Computer vision systems have been incorporated in many real life applications (e.g. surveillance systems, medical imaging, robot navigation and identity verification systems). Object tracking is a key computer vision topic, which aims at detecting the position of a moving object from a video sequence. The appli...

The paper proposes a way of parallel processing of SURF and Optical Flow for moving object recognition and tracking. The object recognition and tracking is one of the most important task in computer vision, however disadvantage are many operations cause processing speed slower so that it can’t do real-time object recognition and tracking. The proposed method uses a typical way of feature extrac...

The paper proposes a new edge-based multi-object tracking framework, MOTEXATION, which deals with tracking multiple objects with occlusions using the Expectation-Maximization (EM) algorithm and a novel edge-based appearance model. In the edge-based appearance model, an object is modelled by a mixture of a non-parametric contour model and a non-parametric edge model using kernel density estimati...

In wireless sensor network energy efficiency, Data security & Network reliability are a few of the most important aspects to be considered while tracking, monitoring and reporting the data. In the object tracking continuous reporting of data is required, which consumes more energy of network. In this paper, the focus is mainly driven over the survey of the energy-efficient object tracking clust...