Object tracking algorithms, when it comes to implementing it on hardware ASIC, it becomes difficult task, due to certain limitations in hardware. This paper shows how mean-shift algorithm is implemented in HDL along with the description of ports and interfaces. Keywords— Object tracking, complexity in hardware ASIC, Mean Shift algorithm, Histogram, Bhattacharya coefficient

Real-time object tracking is a problem which involves extraction of critical information from complex and uncertain imagedata. In this paper, we present a comprehensive methodology to design an artificial neural network (ANN) for a real-time object tracking application. The object, which is tracked for the purpose of demonstration, is a specific airplane. However, the proposed ANN can be traine...

This paper provides a brief overview of ongoing work towards the realisation of a multi-camera video-based person tracking system. The developing system is orientated towards a distributed architecture for sharing visual information between multiple cameras. A hierarchical method for modelling people in scenes using colour features is proposed, however, future development will also look at incl...

A real-time object tracking and collision avoidance method for mobile robot navigation is presented using stereo vision and a laser sensor. Stereo vision is used to identify the target while laser based range measurements are utilized to avoid collision with surrounding objects. The target is tracked by its predetermined or dynamically defined color. Experimental results in indoor environments ...

In this paper, we present a novel method for moving object detection using background subtraction and tracking for lightweight visual surveillance systems. The proposed moving object detection method using background subtraction is based on a “Gaussianity test” and a shading model. The method has been shown to be robust to dynamic scenes such as sudden illumination changes and presence of relat...

A kernel-based metric measuring tracking reliability that is based on discriminative components of a kernel target model and kernel mutual information is presented. The discriminative components of the kernel target model are selected by computing the log-likelihood ratios of classconditional sample densities of these components from a target region and background sampled region. The components...

Shadow detection is useful in many applications like image segmentation, scene interpretation and object recognition/tracking. Shadow in images is formed when direct light from a light source cannot reach due to obstruction by an object. Shadow removal is a critical step for improving object detection and tracking. Many algorithms for shadow detection have been proposed in the literature. This ...

In this chapter, we discuss the problem of tracking objects without having to learn a model of the object’s appearance in advance (i.e., model-free tracking). Object tracking has many practical applications, which motivated continous developments in the field. A particularly successful tracking technique that has been recently proposed is the structured tracker called Struck. Struck uses suppor...