Javier Barandiarán

• M.S. Computer Engineering
• Senior Researcher at Vicomtech

A major challenges of deep learning (DL) is the necessity to collect huge amounts of training data. Often, the lack of a sufficiently large dataset discourages the use of DL in certain applications. Typically, acquiring the required amounts of data costs considerable time, material and effort. To mitigate this problem, the use of synthetic images c...

Lane markings are a key element for Autonomous Driving. The generation of high definition maps and ground-truth data require extensive manual labor. In this paper, we present an efficient and robust method for the offline annotation of lane markings, using low-density LIDAR point clouds and odometry information. The odometry is used to accumulate t...

A major challenges of deep learning (DL) is the necessity to collect huge amounts of training data. Often, the lack of a sufficiently large dataset discourages the use of DL in certain applications. Typically, acquiring the required amounts of data costs considerable time, material and effort. To mitigate this problem, the use of synthetic images c...

This paper introduces a web application for point cloud annotation that is used in the advanced driver assistance systems field. Apart from the point cloud viewer, the web tool has an object viewer and a timeline to define the attributes of the annotations and a video viewer to validate the point cloud annotations with the corresponding video image...

3D image rendering for virtual reality HMDs is typically generated based on a set of parameters taken from the manufacturer-supplied specifications and an idealised perspective model. But actual displays may vary in build features that alter spatial perception. Moreover, the eye focusing effort is often ignored. The resulting visual discomfort and...

Most recent visual odometry algorithms based on sparse feature matching are computationally efficient methods that can be executed in real time on desktop computers. However, further efforts are required to reduce computational complexity in order to integrate these solutions in embedded platforms with low power consumption. This paper presents a s...

In this paper we analyze the recent exponential growth of applications based on video processing in the framework of Advanced Driver Assistance Systems (ADAS). Specifically, we focus on the cost-effective solutions provided by computer vision methods for services like lane departure warning systems, collision avoidance systems, etc. Along the paper...

An automatic method for rail inspection is introduced in this paper. The method detects rail flaws using computer vision algorithms. Unlike other methods designed for the same goal, we propose a method that automatically fits a 3D rail model to the observations. The proposed strategy is based on the novel combination of a simple but effective laser...

This article introduces a 3D vehicle tracking system in a traffic surveillance environment devised for shadow tolling applications. It has been specially designed to operate in real time with high correct detection and classification rates. The system is capable of providing accurate and robust results in challenging road scenarios, with rain, traf...

This article presents a methodology for reconstruction of 3D faces which is based on stereoscopic images of the scene using active and passive surface reconstruction. A sequence of Gray patterns is generated, which are projected onto the scene and their projection recorded by a pair of stereo cameras. The images are rectified to make coincident the...

A new method for 3D vehicle modeling in low-cost monocamera surveillance systems is introduced in this paper. The proposed algorithm aims to resolve the projective ambiguity of 2D image observations by means of the integration of temporal information and model priors within a Markov Chain Monte Carlo (MCMC) method. The method is specially designed...

In this paper we present a reliable depth estimation system which works in real-time with commodity hardware. The system is specially intended for 3D visualization using autostereoscopic displays. The core of this work is an implementation of a modified version of the adaptive support-weight algorithm that includes highly optimized algorithms for G...

Surface reconstruction from unorganized point set is a common problem in computer graphics. Generation of the signed distance field from the point set is a common methodology for the surface reconstruction. The reconstruction of implicit surfaces is made with the algorithm of marching cubes, but the distance field of a point set can not be processe...

This work proposes an extension of the Marching Cubes algorithm, where the goal is to represent implicit functions with higher accuracy using the same grid size. The proposed algorithm displaces the vertices of the cubes iteratively until the stop condition is achieved. After each iteration, the difference between the implicit and the explicit repr...

This work proposes a variation on the Marching Cubes algorithm, where the goal is to represent implicit functions with higher resolution and better graphical qualiry using the same grid size. The proposed algorithm displaces the vertices of the cubes iteratively until the stop condition is achieved. After each iteration, the difference betvveen the...

A novel real-time people counting system is presented in this paper. Using a single overhead mounted camera, the system counts the number of people going in and out of an observed area. Counting is performed by analyzing an image zone composed by a set of virtual counting lines. The system runs on a commercial PC, does not need a special background...

In this paper we present a real-time 3D object tracking algorithm based on edges and using a single pre-calibrated camera. During the tracking process, the algorithm is continuously projecting the 3D model to the current frame by using the pose estimated in the previous frame. Once projected, some control points are generated along the visible edge...