Modern web sites commonly interact with thirdparty domains to integrate advertisements and generate revenue from them. To improve the relevance of advertisements, online advertisers track user activities online with third-party cookies. However, excessive online tracking might cause unreasonable access to users’ browsing information. Users are thus in need of a simple way to control the sharing...

Previous works for multi-target tracking employ two strategies: global optimization and online state estimation. In time-critical applications, the former methods have long temporal latency, and the latter can’t recover from erroneous association or drifting. In this paper, we combine these two strategies, and propose a new low-latency online tracking approach. Unlike previous multi-hypotheses ...

This paper proposes an online tracking method which has been inspired by studying the effects of Scale Invariant Feature Transform (SIFT) when applied to objects assumed to be flat even though they are not. The consequent deviation from flatness induces nuisance factors that act on the feature representation in a manner for which no general local invariants can be computed, such as in the case ...

A simple easy to implement algorithm is proposed to address wall tracking task of an autonomous robot. The robot should navigate in unknown environments, find the nearest wall, and track it solely based on locally sensed data. The proposed method benefits from coupling fuzzy logic and Q-learning to meet requirements of autonomous navigations. Fuzzy if-then rules provide a reliable decision maki...

The intelligence of a mobile robot is highly dependent on its vision. The main objective of an intelligent mobile robot is in its ability to the online image processing, object detection, and especially visual tracking which is a complex task in stochastic environments. Tracking algorithms suffer from sequence challenges such as illumination variation, occlusion, and background clutter, so an a...

The topic of Doppler and Bearing Tracking (DBT) problem is to achieve a target trajectory using the Doppler and Bearing measurements. The difficulty of DBT problem comes from the nonlinearity terms exposed in the measurement equations. Several techniques were studied to deal with this topic, such as the unscented Kalman filter. Nevertheless, the performance of the filter depends directly on the...

Object tracking quality usually depends on video scene conditions (e.g. illumination, density of objects, object occlusion level). In order to overcome this limitation, this article presents a new control approach to adapt the object tracking process to the scene condition variations. More precisely, this approach learns how to tune the tracker parameters to cope with the tracking context varia...

Motivation. Correlation filter based tracking has attracted many researchers’ attention in recent years for high efficiency and robustness. Most existing works [1, 2, 4] focus on exploiting different characteristics with correlation filters for visual tracking, e.g., circulant structure, kernel trick, effective feature representation and context information. Despite its good performance, most o...

Robust visual tracking requires constant update of the target appearance model, but without losing track of previous appearance information. One of the difficulties with the online learning approach to this problem has been a lack of flexibility in the modelling of the inevitable variations in target and scene appearance over time. The traditional online learning approach to the problem treats ...