Ghazaleh Panahandeh

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This paper presents a novel vision-based localization and mapping algorithm using image moments of region features. The environment is represented using regions, such as planes and/or 3D objects instead of only a dense set of feature points. The regions can be uniquely defined using a small number of parameters; e.g., a plane can be completely characterized(More)
In this paper, a novel method for estimating the transformation between an inertial measurement unit (IMU) and a camera together with the intrinsic parameters of the camera is proposed. The method relies on images of reflected feature points in a planar mirror captured by an uncalibrated camera mounted with an IMU. It does not rely on using a fixed(More)
Nonnegative matrix factorization (NMF) has been actively investigated and used in a wide range of problems in the past decade. A significant amount of attention has been given to develop NMF algorithms that are suitable to model time series with strong temporal dependencies. In this paper, we propose a novel state-space approach to perform dynamic NMF(More)
Low-complexity error concealment techniques for missing macroblock (MB) recovery based on the boundary matching principle are extensively studied and evaluated. In this paper, an improved boundary matching algorithm (BMA) using adaptive search is presented to conceal channel errors in inter-frames of video images. The proposed scheme adaptively selects(More)
The idea is to implement a vision-aided inertial navigation system (INS) for estimating inertial measurement unit (IMU)-camera ego-motion. The system consists of a ground facing monocular camera mounted on an IMU that is observing ground plane feature points. The motion estimation procedure is through tracking detected corresponding feature points between(More)
In this paper, we present an observability analysis of a vision-aided inertial navigation system (VINS) in which the camera is downward looking and observes a single point feature on the ground. In our analysis, the full INS parameter vector (including position, velocity, rotation, and inertial sensor biases) as well as the 3D position of the observed point(More)
Postprint This is the accepted version of a paper published in IEEE Transactions on Instrumentation and Measurement. This paper has been peer-reviewed but does not include the final publisher proof-corrections or journal pagination. Access to the published version may require subscription. Abstract—This paper describes a novel and a low-cost calibration(More)
In this paper, a method for determining ground plane features in a sequence of images captured by a mobile camera is presented. The hardware of the mobile system consists of a monocular camera that is mounted on an inertial measurement unit (IMU). An image processing procedure is proposed, first to extract image features and match them across consecutive(More)