Automatically changing the expression and physical features of a face from an input image is a topic that has been traditionally tackled in a 2D domain. In this paper, we bring this problem to 3D and propose a framework ...

This paper addresses the problem of 3D human pose estimation from a single image. We follow a standard two-step pipeline by first detecting the 2D position of the N body joints, and then using these observations to infer ...

We present an approach to the problem of 3D map building in urban settings for service robots, using threedimensional laser range scans as the main data input. Our system is based on the probabilistic alignment of 3D point ...

A novel real-time framework for model-free stereo-video segmentation and stereo-segment tracking is presented, combining real-time optical flow and stereo with image segmentation running separately on two GPUs. The ...

In this paper is presented a deep neural network architecture designed to run on a field-programmable gate array (FPGA) for detection vehicle on LIDAR point clouds. This works present a network based on VoxelNet adapted ...

Water networks are crucial infrastructures for the sustainability of modern cities, and hence their proper operation is of great importance. This includes the fast detection, localization and repair of leaks, which may ...

Time to Contact (TTC) is a biologically inspired method for obstacle detection and reactive control of motion that does not require scene reconstruction or 3D depth estimation. Estimating TTC is difficult because it requires ...

A simplified sewer nework modelling approach based on the hybrid linear systems framework is discussed. It involives both continuous and discrete variables to include a novel approximation of the overflow and flow over ...

This paper proposes a distributed set-membership approach based on zonotopes for interconnected systems with coupled states and unknown-but-bounded uncertainties (both state disturbances and measurement noise). The objective ...