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Real time indoor navigation has lately been a growing field. Some applications might not need a real time estimation of the trajectory, and a post processing framework provides a better estimation of this trajectory. Thus, the aim of this paper is to present and compare three different algorithms to improve a real time trajectory estimation. Two different smoothing algorithms and the Viterbi algorithm...
Digital garage maps are the basis for future vehicle navigation services such as smart parking management that displays the availability of parking spaces. It can direct drivers to empty ones, avoiding any searching, circulating in large, complex parking structures. However, such maps are not currently available, making it impossible to deploy smart parking management. Conducting manual survey incurs...
Indoor localization is an important topic for context aware applications. In particular, many applications for wireless devices can benefit from knowing the location of a user. Despite the huge effort from the research community to solve the localization problem, there is no widely accepted solution for localization in an indoor environment. In this paper we focus on constrained devices and propose...
The missing trajectory problem is a difficulty in various transportation applications, e.g. the road which the truck usually travels and the driver's behavior. Most of previously developed missing data are not concerned about the spatial and continues space. Therefore, in this article, an algorithm is proposed to complete the missing trajectory in a vehicle's trace. The possible traces are found out...
This work presents a trajectory clustering approach that groups trajectories without the need of manually-tuned distance thresholds. Contrary to trajectory clustering approaches that use continuous, often geometrically-motivated similarity measures, path similarity is binary. Similar to homotopy classes, path equivalence is based on the obstacles in the environment. The goal states are, however, not...
This paper considers tracking of objects for video-based intrusion detection systems. Current tracking algorithms can be used for surveillance, but in that use-case, these algorithms execute with too high latency and are not suitable for real-time applications. In this paper, we propose novel techniques for tracking algorithms based on tracklets in order to improve the execution time by limiting the...
The ability to reconsider information over time allows to detect failures and is crucial for long term robust autonomous robot applications. This applies to loop closure decisions in localization and mapping systems. This paper describes a method to analyze all available information up to date in order to robustly remove past incorrect loop closures from the optimization process. The main novelties...
A large percentage of accidents with body injuries in urban areas occur at intersections. Thus, improving safety at intersections using infrastructure based perception systems is desirable. In order to recognize and track the moving objects, a network of laserscanners is used to observe the intersection. In this contribution, a robust object recognition algorithm for vehicles and pedestrians is proposed...
Due to the availability of sattelite- and radio-based location systems in most new devices, it is possible to use geographical location of a node for network management and communication protocol optimization. It is a common belief that usage of location information can bring performance benefits. However, inaccuracy and delay in obtaining such information, together with an associated overhead, can...
A mode seeking algorithm not only can automatically find mode of density of a given data but also can be used for data clustering. However, finding the mode of all data points produce redundant computations. In this paper, a simultaneous mode seeking and clustering which is called Generalized Transport Mean Shift (GTMS) algorithm was proposed. An idea of transportation was used for remedying the problem...
The problem considered in this paper is parameter estimation of a multivariate Gaussian mixture distribution with a known number of components. The paper presents a new Bayesian method which sequentially processes the observed data points by forming candidate sequences of labels assigning data points to mixture components. Using conjugate priors, we derive analytically a recursive formula for the...
In this paper a technique is presented to estimate the traffic intensity for each lane. This method does not require background estimation or even the identification and tracking of individual vehicles. It requires only the identification of each lane and the estimation of a bird eye view of the highway using a rectification method. To each rectified lane, an intensity profile is computed along the...
Motion-based segmentation of a sequence of images is an essential step for many applications of video analysis, including action recognition and surveillance. This paper introduces a new approach to motion segmentation operating on point trajectories. Each of these trajectories has its own start and end instants, hence its own life-span, depending on the pose and appearance changes of the object it...
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