Mature visual experience is tuned by inputs to the developing visual system. However, little is known about the low-level statistics of available visual input as infants interact with the world in rapidly changing ways. Recent studies of the contents of infant-perspective scenes (sampled from a corpus of over 5 million head camera images) indicate that these contents change dramatically over th...

In this paper we derive a model and a method suitable for robot vision to determine the 3D–positions of single flat, not entirely convex objects from crowded scenes holding many fuzzy similar shaped objects. Preferably our approach aims to objects from natural scenes. We propose to use a fast feature based stereo algorithm to match feature positions we compute from the distance transform and th...

This paper reviews FreeWill and other AI architectures that have contributed to the ideas, which underlie it. “FreeWill” proposes and implements a cognitive architecture designed for easy creation of animated scenes with many autonomous agents interacting in various ways. The generation of animated human figures especially in crowd scenes has many applications in such domains as the special eff...

Marker-based and marker-less optical skeletal motion-capture methods use an outside-in arrangement of cameras placed around a scene, with viewpoints converging on the center. They often create discomfort by possibly needed marker suits, and their recording volume is severely restricted and often constrained to indoor scenes with controlled backgrounds. We therefore propose a new method for real...

In this paper we present a simplified tracking method to efficiently track people from a crowd video using the Minimum Mean Square Error (MMSE) technique. The system tracks people from a video sequence and is robust to varied lighting conditions and complex crowded scenes. The method effectively handles small occlusions and invokes a manual tracking procedure under severe occlusions. The system...

Video-surveillance systems are becoming more and more independent in the finding and the exposure of anomalous events. The safety of mankind in crowds under disaster situation is one of the most essential concerns of researchers. This paper presents an approach to notice abnormal situations in crowded scenes by analysing the movement aspect and localize the unusual event using clusterization me...

In most European countries, the first wave of COVID-19 pandemic (spring 2020) led to imposition physical distancing rules, resulting in a drastic and sudden reduction real-life social interactions. Even people not directly affected by virus itself were impacted their and/or mental health, as well financial security, governmental lockdown measures. We investigated whether combination these event...

Removing duplicate proposals is a critical process in pedestrian detection, and usually performed via Non-Maximum Suppression (NMS); however, crowded scenes, the detection of occluded pedestrians are hard to distinguish from proposals, making results inaccurate. In order address above-mentioned problem, authors this paper propose Multi-Attribute NMS (MA-NMS) algorithm, which combines density co...