most citedNasal Patches and Curves for Expression-robust 3D Face Recognition

77 citations · 79 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20192 cited

Filtering Point Targets via Online Learning of Motion Models

Mehryar Emambakhsh, Alessandro Bay, Eduard Vazquez

Filtering point targets in highly cluttered and noisy data frames can be very challenging, especially for complex target motions. Fixed motion models can fail to provide accurate p…

cs.CV201977 cited

Nasal Patches and Curves for Expression-robust 3D Face Recognition

Mehryar Emambakhsh, Adrian Evans

The potential of the nasal region for expression robust 3D face recognition is thoroughly investigated by a novel five-step algorithm. First, the nose tip location is coarsely dete…

cs.CV2018

Convolutional Recurrent Predictor: Implicit Representation for Multi-target Filtering and Tracking

Mehryar Emambakhsh, Alessandro Bay, Eduard Vazquez

Defining a multi-target motion model, which is an important step of tracking algorithms, can be very challenging. Using fixed models (as in several generative Bayesian algorithms,…

cs.CV2018

Deep Recurrent Neural Network for Multi-target Filtering

Mehryar Emambakhsh, Alessandro Bay, Eduard Vazquez

This paper addresses the problem of fixed motion and measurement models for multi-target filtering using an adaptive learning framework. This is performed by defining target tuples…

cs.CV2018

POL-LWIR Vehicle Detection: Convolutional Neural Networks Meet Polarised Infrared Sensors

Marcel Sheeny, Andrew Wallace, Mehryar Emambakhsh +2

For vehicle autonomy, driver assistance and situational awareness, it is necessary to operate at day and night, and in all weather conditions. In particular, long wave infrared (LW…