2,936 research outputs found
Progressive search space reduction for human pose estimation
The objective of this paper is to estimate 2D human pose as a spatial configuration of body parts in TV and movie video shots. Such video material is uncontrolled and extremely challenging. We propose an approach that progressively reduces the search space for body parts, to greatly improve the chances that pose estimation will succeed. This involves two contributions: (i) a generic detector using a weak model of pose to substantially reduce the full pose search space; and (ii) employing ‘grabcut ’ initialized on detected regions proposed by the weak model, to further prune the search space. Moreover, we also propose (iii) an integrated spatiotemporal model covering multiple frames to refine pose estimates from individual frames, with inference using belief propagation. The method is fully automatic and self-initializing, and explains the spatio-temporal volume covered by a person moving in a shot, by soft-labeling every pixel as belonging to a particular body part or to the background. We demonstrate upper-body pose estimation by an extensive evaluation over 70000 frames from four episodes of the TV series Buffy the vampire slayer, and present an application to fullbody action recognition on the Weizmann dataset. 1
2D Articulated Human Pose Estimation and Retrieval in (Almost) Unconstrained Still Images
We present a technique for estimating the spatial layout of humans in still images—the position of the head, torso and arms. The theme we explore is that once a person is localized using an upper body detector, the search for their body parts can be considerably simplified using weak constraints on position and appearance arising from that detection. Our approach is capable of estimating upper body pose in highly challenging uncontrolled images, without prior knowledge of background, clothing, lighting, or the location and scale of the person in the image. People are only required to be upright and seen from the front or the back (not side). We evaluate the stages of our approach experimentally using ground truth layout annotation on a variety of challenging material, such as images from the PASCAL VOC 2008 challenge and video frames from TV shows and feature films. We also propose and evaluate techniques for searching a video dataset for people in a specific pose. To this end, we develop three new pose descriptors and compare their classification and retrieval performance to two baselines built on state-of-the-art object detection model
Streaming flow by oscillating bubbles: Quantitative diagnostics via particle tracking velocimetry
Oscillating microbubbles can be used as microscopic agents. Using external acoustic fields they are able to set the surrounding fluid into motion, Erode surfaces and even to carry particles attached to their interfaces. Although the acoustic streaming flow that the bubble generates in its vicinity has been often observed, it has never been measured and quantitatively compared with the available theoretical models. The scarcity of quantitative data is partially due to the strong three-dimensional character of bubble-induced streaming flows, which demands advanced velocimetry techniques. In this work, we present quantitative measurements of the flow generated by single and pairs of acoustically excited sessile microbubbles using a three-dimensional particle tracking technique. Using this novel experimental approach we are able to obtain the bubble's resonant oscillating frequency, study the boundaries of the linear oscillation regime, give predictions on the flow strength and the shear in the surrounding surface and study the flow and the stability of a two-bubble system. Our results show that velocimetry techniques are a suitable tool to make diagnostics on the dynamics of acoustically excited microbubbles
Pose search: Retrieving people using their pose
We describe a method for retrieving shots containing a particular 2D human pose from unconstrained movie and TV videos. The method involves first localizing the spatial layout of the head, torso and limbs in individual frames using pictorial structures, and associating these through a shot by tracking. A feature vector describing the pose is then constructed from the pictorial structure. Shots can be retrieved either by querying on a single frame with the desired pose, or through a pose classifier trained from a set of pose examples. Our main contribution is an effective system for retrieving people based on their pose, and in particular we propose and investigate several pose descriptors which are person, clothing, background and lighting independent. As a second contribution, we improve the performance over existing methods for localizing upper body layout on unconstrained video. We compare the spatial layout pose retrieval to a baseline method where poses are retrieved using a HOG descriptor. Performance is assessed on five episodes of the TV series ’Buffy the Vampire Slayer’, and pose retrieval is demonstrated also on three Hollywood movies. 1
In vitro and in vivo anti-Trypanosoma cruzi activity of new arylamine Mannich base-type derivatives
Chagas disease is a neglected tropical disease with 6-7 million people infected worldwide and there is no effective treatment. Therefore, there is an urgent need to continue researching in order to discover novel therapeutic alternatives. We present a series of arylaminoketone derivatives as means of identifying new drugs to treat Chagas disease in the acute phase with greater activity, less toxicity and with a larger spectrum of action than that corresponding to the reference drug benznidazole. Indexes of high selectivity found in vitro formed the basis for later in vivo assays in BALB/c mice. Murine model results show that compounds 3, 4, 7 and 10 induced a remarkable decrease in parasitemia levels in acute phase and the parasitemia reactivation following immunosuppression, and curative rates were higher than with benznidazole. These high anti-parasitic activities encourage us to propose these compounds as promising molecules for developing an easy to synthesize anti-Chagas agent
Methods for interpreting lists of affected genes obstained in a DNA microarray experiment
Background - The aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence) and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding) workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for each array, to be used as the starting point for interpreting the affected probes. The data originated from a microarray experiment conducted to study the host reactions in broilers occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. Results - Several conceptually different analytical approaches, using both commercial and public available software, were applied by the participating groups. The following tools were used: Ingenuity Pathway Analysis, MAPPFinder, LIMMA, GOstats, GOEAST, GOTM, Globaltest, TopGO, ArrayUnlock, Pathway Studio, GIST and AnnotationDbi. The main focus of the approaches was to utilise the relation between probes/genes and their gene ontology and pathways to interpret the affected probes/genes. The lack of a well-annotated chicken genome did though limit the possibilities to fully explore the tools. The main results from these analyses showed that the biological interpretation is highly dependent on the statistical method used but that some common biological conclusions could be reached. Conclusion - It is highly recommended to test different analytical methods on the same data set and compare the results to obtain a reliable biological interpretation of the affected genes in a DNA microarray experimen
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