Automatsko brojanje putnika u javnom željezničkom prijevozu uporabom waveleta

Previously, we introduced a passengers’ counting algorithm in public rail transport. The main disadvantage of that algorithm is it lacks automatic event detection. In this article, we implement two automatic wavelet-based passengers counting algorithms. The new algorithms employ the spatial-domain Laplacian-of-Gaussian-based wavelet, and the frequency-domain applied Non-Linear Difference of Gaussians-based wavelet bandpass video scene filters to extract illumination invariant scene features and to combine them efficiently into the background reference frame. Manual segmentation of the scene into rectangles and tiles for detecting an object as seated is no longer needed as we now apply a boundary box tracker on the segmented moving objects’ blobs. A scene map is combined with the wavelet-based methods and the boundary box for multi-camera object registration. We have developed a novel holistic geometrical approach for exploiting the scene map and the recorded video sequences from both cameras installed in each train coach to separate the detected objects and locate their positions on the scene map. We test all the algorithms with several video sequences recorded from the both cameras installed in each train coach. We compare the previously developed non-automatic passengers’ counting algorithm with the two new automatic wavelet-based passengers’ counting algorithms, and an additional spatial-domain automatic non-wavelet based Simple Mixture of Gaussian Models algorithm.U prethodnim radovima uveli smo algoritam za brojanje putnika u javnom željezničkom prijevozu. Glavna manjkavost dosadašnjeg algoritma odsustvo je sustava za automatsko otkrivanje događaja. U ovom radu implementirali smo dva algoritma za automatsko brojanje putnika temeljena na waveletima. Novi algoritmi koriste LoG (Laplacian-of-Gaussian-based) wavelete u prostornoj domeni i pojasne filtre temeljene na waveletima nastalim na nelinearnim razlikama Gaussovih funkcija u frekvencijskoj domeni, pomoću kojih se izdvajaju značajke neosjetljive na razlike u osvjetljenju iz pojedine scene. Te značajke kombiniraju se u referentnu sliku koja prikazuje pozadinu scene. Ručna segmentacija scene u pravokutnike korištena u prethodnom algoritmu više nije potrebna jer se sada koristi automatsko praćenje rubova na segmentiranim objektima. Mapa scene kombinirana je s wavelet metodama i okvirom granica slike u svrhu registracije objekata pomoću više kamera. Razvili smo i novi cjeloviti geometrijski pristup koji koristi mapu scene i snimljeni videozapis iz dvije kamere postavljene u svakom vagonu vlaka pomoću kojeg možemo odvojiti detektirane objekte i locirati njihove položaje na mapi scene. Algoritmi su ispitani na nekoliko videosekvenci snimljenih s dvije kamere u vagonima. Usporedili smo ranije razvijene neautomatske algoritme za brojanje putnika s dva nova algoritma i s jednostavnim MoG algoritmom u prostornoj domeni

Controlling Joint Optimization of Wireless Video Transmission: the PHOENIX Basic Demonstration Platform

A global approach for realistic network-aware joint source and channel system optimization for wireless video transmission is described in this paper. After a description of the information to be exchanged among the system component blocks, the concept of "JSCC/D controllers" is introduced and the implementation of the first "basic chain" demonstrator realized in the framework of the PHOENIX project is described. Simulation results obtained with such first software demonstration platform confirm the validity of the described approach