Integrált 4D filmelőkészítő rendszer

Az integrált 4D filmelőkészítő rendszer (i4D-PS) egyedülálló módon nyújt támogatást filmes szakemberek számára a filmgyártás előkészítési fázisában. Rendszerünkkel lehetőség nyílik a teljes forgatókönyv-tervezési folyamat egyszerűbb megvalósítására különböző valós és virtuális helyszínek szintézisén és háromdimenziós megjelenítésén keresztül. Az így elkészült filmvízió mozgókép formájában megtekinthető, és a forgatás szimulációja során kinyert technikai adatok precízen felhasználhatóak a filmgyártásban

A tool for manipulating huge point clouds

By the evolution of 3D scanning techniques, creating 3D models of real world objects is getting much easier. Beyond the humansized objects one can easily scan complete buildings, roads, squares, or even towns and countries as well. The raw data that scanning technologies, such that LIDARs or photogrammetry based applications can provide are point clouds. The size of such a point cloud can be enormous, with billions of points, and processing and converting it to another format is very costly. Due to this it is important to efficiently visualise large point clouds and make it possible to modify them. In this paper we give a brief overview of point cloud visualisation techniques and describe our system that provides tools to manipulate point clouds by selecting, annotating, deleting, cleaning necessary parts of them

A tool for manipulating huge point clouds : Technical report

By the evolution of 3D scanning techniques, creating 3D models of real world objects is getting much easier. Beyond the human-sized objects one can easily scan complete buildings, roads, squares, or even towns and countries as well. The raw data that scanning technologies, such that LIDARs or photogrammetry based applications can provide are point clouds. The size of such a point cloud can be enormous, with billions of points, and processing and converting it to another format is very costly. Due to this it is important to efficiently visualise large point clouds and make it possible to modify them. In this paper we give a brief overview of point cloud visualisation techniques and describe our system that provides tools to manipulate point clouds by selecting, annotating, deleting, cleaning necessary parts of them

A Brief Survey of Image-Based Depth Upsampling

Recently, there has been remarkable growth of interest in the development and applications of Time-of-Flight (ToF) depth cameras. However, despite the permanent improvement of their characteristics, the practical applicability of ToF cameras is still limited by low resolution and quality of depth measurements. This has motivated many researchers to combine ToF cameras with other sensors in order to enhance and upsample depth images. In this paper, we compare ToF cameras to three image-based techniques for depth recovery, discuss the upsampling problem and survey the approaches that couple ToF depth images with high-resolution optical images. Other classes of upsampling methods are also mentioned

Using genetic algorithms in computer vision : registering images to 3D surface model

This paper shows a successful application of genetic algorithms in computer vision. We aim at building photorealistic 3D models of real-world objects by adding textural information to the geometry. In this paper we focus on the 2D-3D registration problem: given a 3D geometric model of an object, and optical images of the same object, we need to find the precise alignment of the 2D images to the 3D model. We generalise the photo-consistency approach of Clarkson et al. who assume calibrated cameras, thus only the pose of the object in the world needs to be estimated. Our method extends this approach to the case of uncalibrated cameras, when both intrinsic and extrinsic camera parameters are unknown. We formulate the problem as an optimisation and use a genetic algorithm to find a solution. We use semi-synthetic data to study the effects of different parameter settings on the registration. Additionally, experimental results on real data are presented to demonstrate the efficiency of the method

Lidar-based Gait Analysis and Activity Recognition in a 4D Surveillance System

This paper presents new approaches for gait and activity analysis based on data streams of a Rotating Multi Beam (RMB) Lidar sensor. The proposed algorithms are embedded into an integrated 4D vision and visualization system, which is able to analyze and interactively display real scenarios in natural outdoor environments with walking pedestrians. The main focus of the investigations are gait based person re-identification during tracking, and recognition of specific activity patterns such as bending, waving, making phone calls and checking the time looking at wristwatches. The descriptors for training and recognition are observed and extracted from realistic outdoor surveillance scenarios, where multiple pedestrians are walking in the field of interest following possibly intersecting trajectories, thus the observations might often be affected by occlusions or background noise. Since there is no public database available for such scenarios, we created and published a new Lidar-based outdoors gait and activity dataset on our website, that contains point cloud sequences of 28 different persons extracted and aggregated from 35 minutes-long measurements. The presented results confirm that both efficient gait-based identification and activity recognition is achievable in the sparse point clouds of a single RMB Lidar sensor. After extracting the people trajectories, we synthesized a free-viewpoint video, where moving avatar models follow the trajectories of the observed pedestrians in real time, ensuring that the leg movements of the animated avatars are synchronized with the real gait cycles observed in the Lidar stream

News, Ads, Chats, and Property Rights over Algorithms

The success of tech firms rests on their ownership of the algorithms for operating new platforms for the interactions among five groups of stakeholders in the markets of news, ads, and chats: stakeholders from the spheres of politics, journalism, the citizenry, the tech firms themselves, and other firms. Recent regulations that touch on property rights such as the German Netzwerkdurchsetzungsgesetz and the European Directive on Copyright in the Digital Market have turned ownership of algorithms into exclusive ownership. Thereby tech firms obtain also the right to censor and the exclusive right to micro-target clients for advertisers. Coase’s theorem is used to discuss alternative allocations of property rights that could improve the quality of news, ads, and chats