Camera calibration from a translation + planar motion

This paper addresses the problem of camera calibration by exploiting image invariants under camera/object rotation. A novel translation + planar motion is studied here. The 3 × 3 homography mapping corresponding points before and after the motion is exploited to obtain image invariants under perspective projection. The homography is found to form a "rotation conic" under different rotation angles. Apart from the imaged circular points, this conic can also be exploited to find the vanishing point of the rotation axis and this provides extra constraints for camera calibration. A square calibration pattern, which is invariant under a rotation about its center by multiples of π/2 radians, is introduced as a special instantiation of the translation + planar motion. Experiments on synthetic and real data show good precisions in calibration results.postprintThe 8th IASTED International Conference on Signal and Image Processing (SIP 2006), Honolulu, HI., 14-16 August, 2006. In Proceedings of the 8th IASTED International Conference on Signal and Image Processing, 2006, p. 195-20

Perception of noise and Global Illumination: Toward an automatic stopping criterion based on SVM

Unbiased global illumination methods based on stochastical techniques provide photorealistic images. However, they are prone to noise that can only be reduced by increasing the number of processed samples. The problem of finding the number of samples that are required in order to ensure that most observers cannot perceive any noise is still an open issue. In this article, we address this problem focusing on visual perception of noise. However, rather than using known perceptual models, we investigate the use of learning approaches classically used in the field of Artificial Intelligence. Hence, we propose to use such approaches to create a model which is able to learn which image highlights perceptual noise. The learning is performed through the use of a database of examples based on experimentations of noise perception with human users. This model can then be used in any progressive stochastic global illumination method in order to find the visual convergence threshold of different parts of an input image

Parallelism and the software-hardware interface in embedded systems

This thesis by publications addresses issues in the architecture and microarchitecture of next generation, high performance streaming Systems-on-Chip through quantifying the most important forms of parallelism in current and emerging embedded system workloads. The work consists of three major research tracks, relating to data level parallelism, thread level parallelism and the software-hardware interface which together reflect the research interests of the author as they have been formed in the last nine years. Published works confirm that parallelism at the data level is widely accepted as the most important performance leverage for the efficient execution of embedded media and telecom applications and has been exploited via a number of approaches the most efficient being vectorlSIMD architectures. A further, complementary and substantial form of parallelism exists at the thread level but this has not been researched to the same extent in the context of embedded workloads. For the efficient execution of such applications, exploitation of both forms of parallelism is of paramount importance. This calls for a new architectural approach in the software-hardware interface as its rigidity, manifested in all desktop-based and the majority of embedded CPU's, directly affects the performance ofvectorized, threaded codes. The author advocates a holistic, mature approach where parallelism is extracted via automatic means while at the same time, the traditionally rigid hardware-software interface is optimized to match the temporal and spatial behaviour of the embedded workload. This ultimate goal calls for the precise study of these forms of parallelism for a number of applications executing on theoretical models such as instruction set simulators and parallel RAM machines as well as the development of highly parametric microarchitectural frameworks to encapSUlate that functionality.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Algorithms for Image Analysis in Traffic Surveillance Systems

Import 23/07/2015The presence of various surveillance systems in many areas of the modern society is indisputable and the most perceptible are the video surveillance systems. This thesis mainly describes novel algorithm for vision-based estimation of the parking lot occupancy and the closely related topics of pre-processing of images captured under harsh conditions. The developed algorithms have their practical application in the parking guidance systems which are still more popular. One part of this work also tries to contribute to the specific area of computer graphics denoted as direct volume rendering (DVR).Přítomnost nejrůznějších dohledových systémů v mnoha oblastech soudobé společnosti je nesporná a systémy pro monitorování dopravy jsou těmi nejviditelnějšími. Hlavní část této práce se věnuje popisu nového algoritmu pro detekci obsazenosti parkovacích míst pomocí analýzy obrazu získaného z kamerového systému. Práce se také zabývá tématy úzce souvisejícími s předzpracováním obrazu získaného za ztížených podmínek. Vyvinuté algoritmy mají své praktické uplatnění zejména v oblasti pomocných parkovacích systémů, které se stávají čím dál tím více populárními. Jedna část této práce se snaží přispět do oblasti počítačové grafiky označované jako přímá vizualizace objemových dat.Prezenční460 - Katedra informatikyvyhově