1 code implementation • 18 Oct 2020 • Marcel Sheeny, Emanuele De Pellegrin, Saptarshi Mukherjee, Alireza Ahrabian, Sen Wang, Andrew Wallace
To the best of our knowledge, this is the first public radar dataset which provides high-resolution radar images on public roads with a large amount of road actors labelled.
no code implementations • 6 Dec 2019 • Marcel Sheeny, Andrew Wallace, Sen Wang
For high resolution scene mapping and object recognition, optical technologies such as cameras and LiDAR are the sensors of choice.
no code implementations • 7 Apr 2018 • Marcel Sheeny, Andrew Wallace, Mehryar Emambakhsh, Sen Wang, Barry Connor
For vehicle autonomy, driver assistance and situational awareness, it is necessary to operate at day and night, and in all weather conditions.
no code implementations • 31 May 2017 • Nathanael L. Baisa, Deepayan Bhowmik, Andrew Wallace
In this paper, we propose a new long-term visual tracking algorithm, learning discriminative correlation filters and using an online classifier, to track a target of interest in both sparse and crowded video sequences.
no code implementations • 31 May 2017 • Nathanael L. Baisa, Andrew Wallace
We propose a new framework that extends the standard Probability Hypothesis Density (PHD) filter for multiple targets having $N\geq2$ different types based on Random Finite Set theory, taking into account not only background clutter, but also confusions among detections of different target types, which are in general different in character from background clutter.
1 code implementation • 12 May 2017 • Nathanael L. Baisa, Andrew Wallace
First, we extend the standard Probability Hypothesis Density (PHD) filter for multiple type of targets, each with distinct detection properties, to develop multiple target, multiple type filtering, N-type PHD filter, where $N\geq2$, for handling confusions among target types.
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