One popular task under several computer vision applications is camera pose estimation under video sequences. In previous work, several camera pose estimations approaches have been developed and several algorithms have been proposed. Unfortunately, most ...

Camera pose estimation across video sequences is an important issue under several computer vision applications. In previous work, the most popular approach consists on optimization techniques applied over 2D/3D point correspondences for two consecutive ...

Convolutional Neural Networks (CNNs) [1] are the state of the art of image classification that improved accuracy and robustness of machine vision systems at the price of a very high computational cost. This motivated multiple research efforts to ...

Robust object tracking is a crucial enabler of many computer vision applications. An embedded object tracker must, in addition to respecting real-time requirements, robustly update the position of the tracked object in the captured images and be able to ...

Designing useful person re-identification systems for real-world applications requires attention to operational aspects not typically considered in academic research. Here, we focus on the temporal aspect of re-identification; that is, instead of ...

Accurate traffic sign detection, from vehicle-mounted cameras, is an important task for autonomous driving and driver assistance. It is a challenging task especially when the videos acquired from mobile cameras on portable devices are low-quality. In ...

Person re-identification is an open and challenging problem in computer vision. Most of the existing literature has focused on designing solutions which advantage of a supervised phase either to learn an end-to-end solution based on deep learning ...

Smart cameras are image/video acquisition devices that integrate image processing algorithms close to the image sensor, so they can deliver high-level information to a host computer or high-level decision process. In this context, a central issue is the ...

In this paper we address the problem of tracking a specific person among many in non-overlapping camera networks. It is an important problem with many applications in surveillance and security. Given a person to be tracked by initialising the person in ...

In this paper, we propose a Region of Interest(ROI) modulated H.264 video encoder system, based on a distributed object detector-tracker framework, for smart camera networks. Locations of objects of interest, as determined by detector-tracker are used ...

In this paper we present an embedded smart cameras system that performs multiple objects tracking for the control of an automated conveying system. The smart cameras automatically extract scene description models of the conveying environment from ...

Person re-identification is a difficult task due to variations of person pose, scale changes, different illumination, occlusions, to name a few important factors usually diminishing identification performance across different views. In this work, we ...

Active Smart Camera Networks (SCNs) have a wide range of applications in areas such as banks, airports and underground terminals, where it is necessary to monitor open plan spaces reliably and robustly. However, the monitoring efficiency in such ...

The design of multi-camera surveillance system comes with many advantages, for example it facilitates as understanding how flying objects act in a given volume. One possible application is for the observation interaction of birds and calculate their ...

Smart camera systems integrating multi-model image sensors provide better spectral sensitivity and hence better pass-fail decisions. In a given vision system, pre-processing tasks have a ripple effect on output data and pass-fail decision of high level ...

In this paper we present an algorithm, which enables distributed visual sensor networks to autonomously calibrate the network and dynamically build clusters to achieve cooperative object tracking based on state estimation. A main focus is thereby on ...

Extracting per-frame features using convolutional neural networks for real-time processing of video data is currently mainly performed on powerful GPU-accelerated workstations and compute clusters. However, there are many applications such as smart ...