An object tracking algorithm using a novel simple symmetric similarity function between spatially-smoothed kernel-density estimates of the model and target distributions is proposed and tested. The similarity measure is based on the expectation of the density estimates over the model or target images. The density is estimated using radial-basis kernel functions that measure the affinity between...

An application of simultaneous perturbation stochastic approximation (SPSA) algorithm with two measurements per iteration to the problem of object tracking on video is discussed. The upper bound of mean square estimation error is determined in case of once differentiable functional and almost arbitrary noises. Weak restrictions on uncertainty allow to use random sampling instead of full pixelwi...

Wireless Sensor Network has the potentiality to link the physical world with the virtual world by forming a network of sensor nodes. Energy efficient object tracking is one of the main design issues for wireless sensor networks. Energy efficiency is required as the whole WSN is dependent on the power of batteries and the object tracking is required for checking the varying speed of target, targ...

This paper proposes an adaptive shape kernel-based mean shift tracker using a single static camera for the robot vision system. The question that we address in this paper is how to construct such a kernel shape that is adaptive to the object shape. We perform nonlinear manifold learning technique to obtain the low-dimensional shape space which is trained by training data with the same view as t...

Compared with the color histogram, where the position information of each pixel is ignored, a simplified color correlogram (SCC) representation encodes the spatial information explicitly and enables an estimation algorithm to recover the object orientation. This paper analyzes the capability of the SCC (in a kernel based framework) in detecting and estimating object motion and presents a princi...

Tracking a moving object over time is a challenging task. In this paper object to be tracked is manually selected by the user in one video frame and it is tracked in all subsequent frames of the given input video sequence. The work is carried out in two steps. First the object is detected using 64bin colour histogram matching and the object positions in all the video frames is determined to obt...

We will demonstrate an object tracking algorithm that uses a novel simple symmetric similarity function between spatially-smoothed kernel-density estimates of the model and target distributions. The similarity measure is based on the expectation of the density estimates over the model or target images. The density is estimated using radial-basis kernel functions which measure the affinity betwe...

Object tracking is very important for automatic indexing of video content. This work shows tracking of objects directly using compressed MPEG video data. Two sensors, one using motion vectors and the other using DCT coefficients obtained from compressed video stream, provide measurements for the location of the object being tracked. The optimal estimate from the two measurements is found using ...

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...

Video satellites can stare at target areas on the Earth’s surface to obtain high-temporal-resolution remote sensing videos, which make it possible track objects in satellite videos. However, should be noted that object size videos is usually small and has less textural property, moving are easily occluded, puts forward higher requirements for tracker. In order solve above problems, consider ima...