Wide-Field Multi-Parameter FLIM: Long-Term Minimal Invasive Observation of Proteins in Living Cells.

Time-domain Fluorescence Lifetime Imaging Microscopy (FLIM) is a remarkable tool to monitor the dynamics of fluorophore-tagged protein domains inside living cells. We propose a Wide-Field Multi-Parameter FLIM method (WFMP-FLIM) aimed to monitor continuously living cells under minimum light intensity at a given illumination energy dose. A powerful data analysis technique applied to the WFMP-FLIM data sets allows to optimize the estimation accuracy of physical parameters at very low fluorescence signal levels approaching the lower bound theoretical limit. We demonstrate the efficiency of WFMP-FLIM by presenting two independent and relevant long-term experiments in cell biology: 1) FRET analysis of simultaneously recorded donor and acceptor fluorescence in living HeLa cells and 2) tracking of mitochondrial transport combined with fluorescence lifetime analysis in neuronal processes

Human mobility monitoring in very low resolution visual sensor network

This paper proposes an automated system for monitoring mobility patterns using a network of very low resolution visual sensors (30 30 pixels). The use of very low resolution sensors reduces privacy concern, cost, computation requirement and power consumption. The core of our proposed system is a robust people tracker that uses low resolution videos provided by the visual sensor network. The distributed processing architecture of our tracking system allows all image processing tasks to be done on the digital signal controller in each visual sensor. In this paper, we experimentally show that reliable tracking of people is possible using very low resolution imagery. We also compare the performance of our tracker against a state-of-the-art tracking method and show that our method outperforms. Moreover, the mobility statistics of tracks such as total distance traveled and average speed derived from trajectories are compared with those derived from ground truth given by Ultra-Wide Band sensors. The results of this comparison show that the trajectories from our system are accurate enough to obtain useful mobility statistics

Realizing the Hydrogen Economy through Semantic Web Technologies

The FUSION (Fuel Cell Understanding through Semantic Inferencing, Ontologies and Nanotechnology) project applies, extends, and combines Semantic Web technologies and image analysis techniques to develop a knowledge management system to optimize the design of fuel cells

Spectral 3D Computer Vision -- A Review

Spectral 3D computer vision examines both the geometric and spectral properties of objects. It provides a deeper understanding of an object's physical properties by providing information from narrow bands in various regions of the electromagnetic spectrum. Mapping the spectral information onto the 3D model reveals changes in the spectra-structure space or enhances 3D representations with properties such as reflectance, chromatic aberration, and varying defocus blur. This emerging paradigm advances traditional computer vision and opens new avenues of research in 3D structure, depth estimation, motion analysis, and more. It has found applications in areas such as smart agriculture, environment monitoring, building inspection, geological exploration, and digital cultural heritage records. This survey offers a comprehensive overview of spectral 3D computer vision, including a unified taxonomy of methods, key application areas, and future challenges and prospects

Detail-preserving and Content-aware Variational Multi-view Stereo Reconstruction

Accurate recovery of 3D geometrical surfaces from calibrated 2D multi-view images is a fundamental yet active research area in computer vision. Despite the steady progress in multi-view stereo reconstruction, most existing methods are still limited in recovering fine-scale details and sharp features while suppressing noises, and may fail in reconstructing regions with few textures. To address these limitations, this paper presents a Detail-preserving and Content-aware Variational (DCV) multi-view stereo method, which reconstructs the 3D surface by alternating between reprojection error minimization and mesh denoising. In reprojection error minimization, we propose a novel inter-image similarity measure, which is effective to preserve fine-scale details of the reconstructed surface and builds a connection between guided image filtering and image registration. In mesh denoising, we propose a content-aware $\ell_{p}$-minimization algorithm by adaptively estimating the $p$ value and regularization parameters based on the current input. It is much more promising in suppressing noise while preserving sharp features than conventional isotropic mesh smoothing. Experimental results on benchmark datasets demonstrate that our DCV method is capable of recovering more surface details, and obtains cleaner and more accurate reconstructions than state-of-the-art methods. In particular, our method achieves the best results among all published methods on the Middlebury dino ring and dino sparse ring datasets in terms of both completeness and accuracy.Comment: 14 pages,16 figures. Submitted to IEEE Transaction on image processin

The multifunctional autophagy pathway in the human malaria parasite, Plasmodium falciparum.

Autophagy is a catabolic pathway typically induced by nutrient starvation to recycle amino acids, but can also function in removing damaged organelles. In addition, this pathway plays a key role in eukaryotic development. To date, not much is known about the role of autophagy in apicomplexan parasites and more specifically in the human malaria parasite Plasmodium falciparum. Comparative genomic analysis has uncovered some, but not all, orthologs of autophagy-related (ATG) genes in the malaria parasite genome. Here, using a genome-wide in silico analysis, we confirmed that ATG genes whose products are required for vesicle expansion and completion are present, while genes involved in induction of autophagy and cargo packaging are mostly absent. We subsequently focused on the molecular and cellular function of P. falciparum ATG8 (PfATG8), an autophagosome membrane marker and key component of the autophagy pathway, throughout the parasite asexual and sexual erythrocytic stages. In this context, we showed that PfATG8 has a distinct and atypical role in parasite development. PfATG8 localized in the apicoplast and in vesicles throughout the cytosol during parasite development. Immunofluorescence assays of PfATG8 in apicoplast-minus parasites suggest that PfATG8 is involved in apicoplast biogenesis. Furthermore, treatment of parasite cultures with bafilomycin A 1 and chloroquine, both lysosomotropic agents that inhibit autophagosome and lysosome fusion, resulted in dramatic morphological changes of the apicoplast, and parasite death. Furthermore, deep proteomic analysis of components associated with PfATG8 indicated that it may possibly be involved in ribophagy and piecemeal microautophagy of the nucleus. Collectively, our data revealed the importance and specificity of the autophagy pathway in the malaria parasite and offer potential novel therapeutic strategies