Tracking multiple people online and in real time Report Title We cast the problem of tracking several people as a graph partitioning problem that takes the form of an NP-hard binary integer program. We propose a tractable, approximate, online solution through the combination of a multistage cascade and a sliding temporal window. Our experiments demonstrate significant accuracy improvement over ...

Most defect-tracking systems provide canned reports and the ability to create custom reports. These reports provide a snapshot of the defects in the system and allow different types of filters to be applied. However, all these reports provide limited insights into the defects of a product and often, the reports are operational or tactical in nature. Defect Analytics uses OLAP on a defects repos...

Tracking people across multiple cameras is a challenging research area in visual computing, especially when these cameras have non-overlapping field of views. The important task is to associate a current subject with other prior appearances of the same subject across time and space in a camera network. Several known techniques rely on Bayesian approaches to perform the matching task. However, t...

This paper argues for a joint development of an eye gaze -based, on-line communication aid running on a standard PC with a web -camera. Tracking software is to be provided as open source to allow for improvements and individual integrations with other aids. The interface design shall be defined by the achieved resolution of the tr acking system. The design of a type -to-talk system with 12 larg...

We pursue a research direction that will empower machines with simultaneous tracking and recognition capabilities similar to human cognition. Toward that, we develop algorithms that leverage prior knowledge/model obtained offline with information available online via novel learning algorithms. While humans can effortlessly locate moving objects in different environments, visual tracking remains...

this paper presents an indirect adaptive system based on neuro-fuzzy approximators for the speed control of induction motors. the uncertainty including parametric variations, the external load disturbance and unmodeled dynamics is estimated and compensated by designing neuro-fuzzy systems. the contribution of this paper is presenting a stability analysis for neuro-fuzzy speed control of inducti...

We consider the problem of online subspace tracking of a partially observed high-dimensional data stream corrupted by noise, where we assume that the data lie in a low-dimensional linear subspace. This problem is cast as an online low-rank tensor completion problem. We propose a novel online tensor subspace tracking algorithm based on the CANDECOMP/PARAFAC (CP) decomposition, dubbed OnLine Low-...

Payment is an important factor in a purchase transaction. Ease of payment is a convenience factor in shopping. The easier way of payment of the service users will be more comfortable in the shop. The conditions will be different if the groceries are many and varied and the quality but the payment difficulties. In this research will be investigated whether the payment model most widely used on t...

We address the problem of online de-noising a stream of input points. We assume that the clean data is embedded in a linear subspace. We present two online algorithms for tracking subspaces and, as a consequence, de-noising. We also describe two regularization schemas which improve the resistance to noise. We analyze the algorithms in the loss bound model, and specify some of their properties. ...

In this paper, we propose and study a novel visual object tracking approach based on convolutional networks and recurrent networks. The proposed approach is distinct from the existing approaches to visual object tracking, such as filtering-based ones and tracking-by-detection ones, in the sense that the tracking system is explicitly trained off-line to track anonymous objects in a noisy environ...