When a person taps a foot in time with a piece of music, they are performing beat tracking. Beat tracking is fundamental to the understanding of musical structure, and therefore an essential ability for any system which purports to exhibit musical intelligence or understanding. We present an off-line multiple agent beat tracking system which estimates the locations of musical beats in MIDI perf...

Tracking with a discriminative classifier becomes popular recently. The online updating makes it easy to adapt to target appearance variations. However, this also brings drifting problem. It’s necessary to find a tracking method with strong adaptivity and anti-drifting ability. In this paper, an online semi-supervised boosting method is proposed at first, and based on it, we propose a novel tra...

Online trackers compile profiles on users for targeting ads, customizing websites, and selling users’ information. In this paper, we report on the first detailed study of the perceived benefits and risks of tracking—and the reasons behind them—conducted in the context of users’ own browsing histories. Prior work has studied this in the abstract; in contrast, we collected browsing histories from...

It is a challenging task to develop effective and efficient appearance models for robust object tracking due to factors such as pose variation, illumination change, occlusion, and motion blur. Existing online tracking algorithms often update models with samples from observations in recent frames. While much success has been demonstrated, numerous issues remain to be addressed. First, while thes...

Online tracking has shown to be successful in tracking of previously unknown objects. However, there are two important factors which lead to drift problem of online tracking, the one is how to select the exact labeled samples even when the target locations are inaccurate, and the other is how to handle the confusors which have similar features with the target. In this article, we propose a robu...

This paper proposes a unified approach on tracking and recognition .Object tracking is done at low level and recognition is done at high level. Traditional tracking methods give importance to low level image correspondences between frames. High level image correspondences are used for reliable tracking. Online and Offline models are used for both tracking and recognition which is done simultane...

BACKGROUND Web-based interventions with a self-tracking component have been found to be effective in promoting adults' fruit and vegetable consumption. However, these interventions primarily focus on individual- rather than group-based self-tracking. The rise of social media technologies enables sharing and comparing self-tracking records in a group context. Therefore, we developed an online gr...

We present a new form of online tracking: explicit, yet unnecessary leakage of personal information and detailed shopping habits from online merchants to payment providers. In contrast to the widely debated tracking of Web browsing, online shops make it impossible for their customers to avoid this dissemination of their data. We record and analyse leakage patterns for the 881 most popular US We...

Digital forensics is an emerging field that has uniquely brought together academics, practitioners and law enforcement. Research in this area was inspired by the numerous challenges posed by the increased sophistication of criminal tools. Traditionally, digital forensics has been confined to the extraction of digital evidence from electronic devices. This direct extraction of digital evidence, ...

Online video lectures are becoming commonplace in higher education. One problem is that the instructor might block what he has written on the board. In our project, we reconstruct the online lecture video so that the information on the whiteboard is always available to the viewers. The background subtraction, object tracking, and object replacement technique have been used to reconstruct the mo...