Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

Adaptive uncertain information fusion to enhance plan selection in BDI agent systems

Correctly modelling and reasoning with uncertain information from heterogeneous sources in large-scale systems is critical when the reliability is unknown and we still want to derive adequate conclusions. To this end, context-dependent merging strategies have been proposed in the literature. In this paper we investigate how one such context-dependent merging strategy (originally defined for possibility theory), called largely partially maximal consistent subsets (LPMCS), can be adapted to Dempster-Shafer (DS) theory. We identify those measures for the degree of uncertainty and internal conflict that are available in DS theory and show how they can be used for guiding LPMCS merging. A simplified real-world power distribution scenario illustrates our framework. We also briefly discuss how our approach can be incorporated into a multi-agent programming language, thus leading to better plan selection and decision making.

An Event Driven Fusion Approach for Enjoyment Recognition in Real-time

Social signals and interpretation of carried information is of high importance in Human Computer Interaction. Often used for affect recognition, the cues within these signals are displayed in various modalities. Fusion of multi-modal signals is a natural and interesting way to improve automatic classification of emotions transported in social signals. Throughout most present studies, uni-modal affect recognition as well as multi-modal fusion, decisions are forced for fixed annotation segments across all modalities. In this paper, we investigate the less prevalent approach of event driven fusion, which indirectly accumulates asynchronous events in all modalities for final predictions. We present a fusion approach, handling short-timed events in a vector space, which is of special interest for real-time applications. We compare results of segmentation based uni-modal classification and fusion schemes to the event driven fusion approach. The evaluation is carried out via detection of enjoyment-episodes within the audiovisual Belfast Story-Telling Corpus.

IHG-1 increases mitochondrial fusion and bioenergetic function

Induced in high glucose-1 (IHG-1) is a conserved mitochondrial protein associated with diabetic nephropathy (DN) that amplifies profibrotic transforming growth factor (TGF)-β1 signaling and increases mitochondrial biogenesis. Here we report that inhibition of endogenous IHG-1 expression results in reduced mitochondrial respiratory capacity, ATP production, and mitochondrial fusion. Conversely, overexpression of IHG-1 leads to increased mitochondrial fusion and also protects cells from reactive oxygen species-induced apoptosis. IHG-1 forms complexes with known mediators of mitochondrial fusion-mitofusins (Mfns) 1 and 2-and enhances the GTP-binding capacity of Mfn2, suggesting that IHG-1 acts as a guanine nucleotide exchange factor. IHG-1 must be localized to mitochondria to interact with Mfn1 and Mfn2, and this interaction is necessary for increased IHG-1-mediated mitochondrial fusion. Together, these findings indicate that IHG-1 is a novel regulator of both mitochondrial dynamics and bioenergetic function and contributes to cell survival following oxidant stress. We propose that in diabetic kidney disease increased IHG-1 expression protects cell viability and enhances the actions of TGF-β, leading to renal proximal tubule dedifferentiation, an important event in the pathogenesis of this devastating condition.

Towards a general framework for information fusion

Depending on the representation setting, different combination rules have been proposed for fusing information from distinct sources. Moreover in each setting, different sets of axioms that combination rules should satisfy have been advocated, thus justifying the existence of alternative rules (usually motivated by situations where the behavior of other rules was found unsatisfactory). These sets of axioms are usually purely considered in their own settings, without in-depth analysis of common properties essential for all the settings. This paper introduces core properties that, once properly instantiated, are meaningful in different representation settings ranging from logic to imprecise probabilities. The following representation settings are especially considered: classical set representation, possibility theory, and evidence theory, the latter encompassing the two other ones as special cases. This unified discussion of combination rules across different settings is expected to provide a fresh look on some old but basic issues in information fusion.

Evidential Fusion for Gender Profiling

Gender profiling is a fundamental task that helps CCTV systems to
provide better service for intelligent surveillance. Since subjects being detected
by CCTVs are not always cooperative, a few profiling algorithms are proposed
to deal with situations when faces of subjects are not available, among which
the most common approach is to analyze subjects’ body shape information. In
addition, there are some drawbacks for normal profiling algorithms considered
in real applications. First, the profiling result is always uncertain. Second, for a
time-lasting gender profiling algorithm, the result is not stable. The degree of
certainty usually varies, sometimes even to the extent that a male is classified
as a female, and vice versa. These facets are studied in a recent paper [16] using
Dempster-Shafer theory. In particular, Denoeux’s cautious rule is applied for
fusion mass functions through time lines. However, this paper points out that if
severe mis-classification is happened at the beginning of the time line, the result
of applying Denoeux’s rule could be disastrous. To remedy this weakness,
in this paper, we propose two generalizations to the DS approach proposed in
[16] that incorporates time-window and time-attenuation, respectively, in applying
Denoeux’s rule along with time lines, for which the DS approach is a special
case. Experiments show that these two generalizations do provide better results
than their predecessor when mis-classifications happen.

Fusion of Static and Temporal Information for Threat Evaluation in Sensor Networks

In many CCTV and sensor network based intelligent surveillance systems, a number of attributes or criteria are used to individually evaluate the degree of potential threat of a suspect. The outcomes for these attributes are in general from analytical algorithms where data are often pervaded with uncertainty and incompleteness. As a result, such individual threat evaluations are often inconsistent, and individual evaluations can change as time elapses. Therefore, integrating heterogeneous threat evaluations with temporal influence to obtain a better overall evaluation is a challenging issue. So far, this issue has rarely be considered by existing event reasoning frameworks under uncertainty in sensor network based surveillance. In this paper, we first propose a weighted aggregation operator based on a set of principles that constraints the fusion of individual threat evaluations. Then, we propose a method to integrate the temporal influence on threat evaluation changes. Finally, we demonstrate the usefulness of our system with a decision support event modeling framework using an airport security surveillance scenario.

Relationships between EEA1 binding partners and their role in endosome fusion

Homotypic fusion between early endosomes requires the phosphatidylinositol 3-phosphate (PI3P)-binding protein, Early Endosomal Autoantigen 1 (EEA1). We have investigated the role of other proteins that interact with EEA1 in the fusion of early endosomes derived from Baby Hamster Kidney (BHK) cells. We confirm a requirement for syntaxin 13, but additionally show that the assay is equally sensitive to reagents specifically targeted against syntaxin 6. Binding of EEA1 to immobilised GST-syntaxin 6 and 13 was directly compared; only syntaxin 6 formed a stable complex with EEA1. Early endosome fusion requires the release of intravesicular calcium, and calmodulin plays a vital role in the fusion pathway, as judged by sensitivity to antagonists. We demonstrate that both EEA1 and syntaxin 13 interact with calmodulin. In the case of EEA1, binding to calmodulin requires an IQ domain, which is adjacent to a C-terminal FYVE domain that specifically binds to PI3P. We have assessed the influence of protein binding partners on EEA1 interaction with PI3P and find that both calmodulin and rab5-GTP are antagonistic to PI3P binding, whilst syntaxins 6 and 13 have no effect. These studies reveal a complex network of interactions between the proteins required for endosome fusion.

Regulation of endosome fusion

Homotypic fusion between early endosomes can be reconstituted in vitro. By using wortmannin and LY294002, inhibitors of phosphatidylinositol (Pl) 3-kinase, a requirement for this activity has been established in order for fusion to proceed efficiently. It has been shown that Pl 3-kinase activity is required downstream of rab5 activation, although a large excess of activated rab5 can overcome wortmannin inhibition. A series of experiments have also been performed which indicate a role for early endosomal autoantigen 1 (EEA1) in determining fusion efficiency. EEA1 dissociates from membranes following wortmannin treatment. It is proposed that the requirement of endosome fusion for Pl 3-kinase activity is to promote the association of EEA1 with endosomes.

Involvement of the endosomal autoantigen EEA1 in homotypic fusion of early endosomes

In mammalian cells, fusion between early endocytic vesicles has been shown to require the ubiquitous intracellular fusion factors N-ethylmaleimide-sensitive factor (NSF) and alpha-SNAP, as well as a factor specific for early endosomes, the small GTPase Rab5 [1-3]. We have previously demonstrated an additional requirement for phosphatidylinositol 3-kinase (PI 3-kinase) activity [4]. The membrane association of early endosomal antigen 1 (EEA1), a specific marker of early endosomes [5,6], has recently been shown to be similarly dependent on PI 3-kinase activity [7], and we therefore postulated that it might be involved in endosome fusion. Here, we present evidence that EEA1 has an important role in determining the efficiency of endosome fusion in vitro. Both the carboxy-terminal domain of EEA1 (residues 1098-1411) and specific antibodies against EEA1 inhibited endosome fusion when included in an in vitro assay. Furthermore, depletion of EEA1, both from the membrane fraction used in the assay by washing with salt and from the cytosol using an EEA1-specific antibody, resulted in inhibition of endosome fusion. The involvement of EEA1 in endosome fusion accounts for the sensitivity of the endosome fusion assay to inhibitors of PI 3-kinase.

Inhibition of endosome fusion by wortmannin persists in the presence of activated Rab5

Rab5-dependent endosome fusion is sensitive to the phosphoinositide 3-kinase inhibitor, wortmannin. It has been proposed that phosphoinositide 3-kinase activity may be required for activation of rab5 by influencing its nucleotide cycle such as to promote its active GTP state. In this report we demonstrate that endosome fusion remains sensitive to wortmannin despite preloading of endosomes with stimulatory levels of a GTPase-defective mutant rab5(Q79L) or of a xanthosine triphosphate-binding mutant, rab5(D136N), in the presence of the nonhydrolysable analogue XTPgammaS. These results suggest that activation of rab5 cannot be the principal function of the wortmannin-sensitive factor on the endosome fusion pathway. This result is extrapolated to all GTPases by demonstrating that endosome fusion remains wortmannin sensitive despite prior incubation with the nonhydrolysable nucleotide analogue GTPgammaS. Consistent with these results, direct measurement of clathrin-coated vesicle-stimulated nucleotide dissociation from exogenous rab5 was insensitive to the presence of wortmannin. A large excess of rab5(Q79L), beyond levels required for maximal stimulation of the fusion assay, afforded protection against wortmannin inhibition, and partial protection was also observed with an excess of wild-type rab5 independent of GTPgammaS.

An evidential fusion approach for gender profiling

CCTV (Closed-Circuit TeleVision) systems are broadly deployed in the present world. To ensure in-time reaction for intelligent surveillance, it is a fundamental task for real-world applications to determine the gender of people of interest. However, normal video algorithms for gender profiling (usually face profiling) have three drawbacks. First, the profiling result is always uncertain. Second, the profiling result is not stable. The degree of certainty usually varies over time, sometimes even to the extent that a male is classified as a female, and vice versa. Third, for a robust profiling result in cases that a person’s face is not visible, other features, such as body shape, are required. These algorithms may provide different recognition results - at the very least, they will provide different degrees of certainties. To overcome these problems, in this paper, we introduce an Dempster-Shafer (DS) evidential approach that makes use of profiling results from multiple algorithms over a period of time, in particular, Denoeux’s cautious rule is applied for fusing mass functions through time lines. Experiments show that this approach does provide better results than single profiling results and classic fusion results. Furthermore, it is found that if severe mis-classification has occurred at the beginning of the time line, the combination can yield undesirable results. To remedy this weakness, we further propose three extensions to the evidential approach proposed above incorporating notions of time-window, time-attenuation, and time-discounting, respectively. These extensions also applies Denoeux’s rule along with time lines and take the DS approach as a special case. Experiments show that these three extensions do provide better results than their predecessor when mis-classifications occur.