Gait-based carried object detection using persistent homology

There are surveillance scenarios where it is important to emit an alarm when a person carrying an object is detected. In order to detect when a person is carrying an object, we build models of naturally-walking and object-carrying persons using topological features. First, a stack of human silhouettes, extracted by background subtraction and thresholding, are glued through their gravity centers, forming a 3D digital image I. Second, different filters (i.e. orderings of the cells) are applied on ∂ K(I) (cubical complex obtained from I) which capture relations among the parts of the human body when walking. Finally, a topological signature is extracted from the persistence diagrams according to each filter. We build some clusters of persons walking naturally, without carrying object and some clusters of persons carrying bags. We obtain vector prototypes for each cluster. Simple distances to the means are calculated for detecting the presence of carrying object. The measure cosine is used to give a similarity value between topological signatures. The accuracies obtained are 95.7% and 95.9% for naturally-walking and object-carrying respectively

Joint Tracking and Event Analysis for Carried Object Detection

This paper proposes a novel method for jointly estimating the track of a moving object and the events in which it participates. The method is intended for dealing with generic objects that are hard to localise and track with the performance of current detection algorithms - our focus is on events involving carried objects. The tracks for other objects with which the target object interacts (e.g. the carrying person) are assumed to be given. The method is posed as maximisation of a posterior probability defined over event sequences and temporally-disjoint subsets of the tracklets from an earlier tracking process. The probability function is a Hidden Markov Model coupled with a term that penalises non-smooth tracks and large gaps in the observed data. We evaluate the method using tracklets output by three state of the art trackers on the new created MINDSEYE2015 dataset and demonstrate improved performance

Qualitative and quantitative spatio-temporal relations in daily living activity recognition

For the effective operation of intelligent assistive systems working in real-world human environments, it is important to be able to recognise human activities and their intentions. In this paper we propose a novel approach to activity recognition from visual data. Our approach is based on qualitative and quantitative spatio-temporal features which encode the interactions between human subjects and objects in an efficient manner. Unlike the state of the art, our approach uses significantly fewer assumptions and does not require knowledge about object types, their affordances, or the sub-level activities that high-level activities consist of. We perform an automatic feature selection process which provides the most representative descriptions of the learnt activities. We validated the method using these descriptions on the CAD-120 benchmark dataset, consisting of video sequences showing humans performing daily real-world activities. The method is shown to outperform state of the art benchmarks

Context aware detection and tracking

This paper presents a novel approach to incorporate multiple contextual factors into a tracking process, for the purpose of reducing false positive detections. While much previous work has focused on improving object detection on static images using context, these have not been integrated into the tracking process. Our hypothesis is that a significant improvement can result from the use of context in dynamically influencing the linking of object detections, during the tracking process. To verify this hypothesis, we augment a state of the art dynamic programming based tracker with contextual information by reformulating the maximum a posteriori (MAP) estimation formulation. This formulation introduces contextual factors that first of all augment detection strengths and secondly provides temporal context. We allow both these types of factors to contribute organically to the linking process by learning the relative contribution of each of these factors jointly during a gradient decent based optimisation process. Our experiments demonstrate that the proposed approach contributes to a significantly superior performance on a recent challenging video dataset, which captures complex scenes with a wide range of object types and diverse backgrounds

Carried object detection and tracking using geometric shape models and spatio-temporal consistency

This paper proposes a novel approach that detects and tracks carried objects by modelling the person-carried object relationship that is characteristic of the carry event. In order to detect a generic class of carried objects, we propose the use of geometric shape models, instead of using pre-trained object class models or solely relying on protrusions. In order to track the carried objects, we propose a novel optimization procedure that combines spatio-temporal consistency characteristic of the carry event, with conventional properties such as appearance and motion smoothness respectively. The proposed approach substantially outperforms a state-of-the-art approach on two challenging datasets PETS2006 and MINDSEYE2012

Approaches in biotechnological applications of natural polymers

Natural polymers, such as gums and mucilage, are biocompatible, cheap, easily available and non-toxic materials of native origin. These polymers are increasingly preferred over synthetic materials for industrial applications due to their intrinsic properties, as well as they are considered alternative sources of raw materials since they present characteristics of sustainability, biodegradability and biosafety. As definition, gums and mucilages are polysaccharides or complex carbohydrates consisting of one or more monosaccharides or their derivatives linked in bewildering variety of linkages and structures. Natural gums are considered polysaccharides naturally occurring in varieties of plant seeds and exudates, tree or shrub exudates, seaweed extracts, fungi, bacteria, and animal sources. Water-soluble gums, also known as hydrocolloids, are considered exudates and are pathological products; therefore, they do not form a part of cell wall. On the other hand, mucilages are part of cell and physiological products. It is important to highlight that gums represent the largest amounts of polymer materials derived from plants. Gums have enormously large and broad applications in both food and non-food industries, being commonly used as thickening, binding, emulsifying, suspending, stabilizing agents and matrices for drug release in pharmaceutical and cosmetic industries. In the food industry, their gelling properties and the ability to mold edible films and coatings are extensively studied. The use of gums depends on the intrinsic properties that they provide, often at costs below those of synthetic polymers. For upgrading the value of gums, they are being processed into various forms, including the most recent nanomaterials, for various biotechnological applications. Thus, the main natural polymers including galactomannans, cellulose, chitin, agar, carrageenan, alginate, cashew gum, pectin and starch, in addition to the current researches about them are reviewed in this article.. }To the Conselho Nacional de Desenvolvimento Cientfíico e Tecnológico (CNPq) for fellowships (LCBBC and MGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nvíel Superior (CAPES) (PBSA). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and COMPETE 2020 (POCI-01-0145-FEDER-006684) (JAT)

Opium addiction is associated with increased damage to cardiomyocytes: Protective roles played by apelins

Background: It has been reported that opium can deteriorate the complications of acute myocardial infarction (AMI). Apelins are molecules whose protective roles against cardiomyocytes have been documented previously. The aim of this study was to evaluate the effects of opium on the serum apelin levels in patients with AMI.Methods: This study was performed on 60 patients with AMI (30 addicted and 30 nonaddicted). The serum levels of apelins, low-density lipoprotein, high-density lipoprotein, triglyceride, cholesterol, total creatine phosphokinase (CPK), and CPK-MB were evaluated using commercial kits.Results: The results showed that although the serum level of apelins was not different between the addicted and nonaddicted patients, it was significantly associated with heart rate and CPK levels in the addicted patients.Conclusions: Considering our results, opium addiction may be associated with increased damage to cardiomyocytes. Additionally, the positive association between apelins and CPK may indicate the protective roles played by these molecules during AMI. (Iranian Heart Journal 2020; 21(3): 6-14). © 2020, Iranian Heart Association. All rights reserved