Conventional image-motion based methods for structure from motion first compute optical flow, then solve for the 3D motion parameters based on the epipolar constraint, and finally recover the 3D geometry of the scene. However, errors in optical flow …
Automated surveillance is essential for the protection of Critical Infrastructures (CIs) in future Smart Cities. The dynamic environments and bandwidth requirements demand systems that adapt themselves to react when events of interest occur. We …
Indoor monitoring of people at their homes has become a popular application in Smart Health. With the advances in Machine Learning and hardware for embedded devices, new distributed approaches for Cyber-Physical Systems (CPSs) are enabled. Also, …
By looking at a person’s hands, one can often tell what the person is going to do next, how his/her hands are moving and where they will be, because an actor’s intentions shape his/her movement kinematics during action execution. Similarly, active …
Clustering is crucial for many computer vision applications such as robust tracking, object detection and segmentation. This work presents a real-time clustering technique that takes advantage of the unique properties of event-based vision sensors. …
Standardized benchmarks in Computer Vision have greatly contributed to the advance of approaches to many problems in the field. If we want to enhance the visibility of event-driven vision and increase its impact, we will need benchmarks that allow …
This work presents an FPGA implementation of a highly parallel architecture for the motion and disparity estimations of color images. Our system implements the well-known Lucas & Kanade algorithm with multi-scale extension for the computation of …
The bio-inspired, asynchronous event-based dynamic vision sensor records temporal changes in the luminance of the scene at high temporal resolution. Since events are only triggered at significant luminance changes, most events occur at the boundary …
This paper compares image motion estimation with asynchronous event-based cameras to Computer Vision approaches using as input frame-based video sequences. Since dynamic events are triggered at significant intensity changes, which often are at the …
We describe an intelligent scheme to condense dense vision features, efficiently reducing the size of representation maps and keeping relevant information for further processing during subsequent stages. We have integrated our condensation algorithm …