31,451 research outputs found

    Interactive inspection of complex multi-object industrial assemblies

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    The final publication is available at Springer via http://dx.doi.org/10.1016/j.cad.2016.06.005The use of virtual prototypes and digital models containing thousands of individual objects is commonplace in complex industrial applications like the cooperative design of huge ships. Designers are interested in selecting and editing specific sets of objects during the interactive inspection sessions. This is however not supported by standard visualization systems for huge models. In this paper we discuss in detail the concept of rendering front in multiresolution trees, their properties and the algorithms that construct the hierarchy and efficiently render it, applied to very complex CAD models, so that the model structure and the identities of objects are preserved. We also propose an algorithm for the interactive inspection of huge models which uses a rendering budget and supports selection of individual objects and sets of objects, displacement of the selected objects and real-time collision detection during these displacements. Our solution–based on the analysis of several existing view-dependent visualization schemes–uses a Hybrid Multiresolution Tree that mixes layers of exact geometry, simplified models and impostors, together with a time-critical, view-dependent algorithm and a Constrained Front. The algorithm has been successfully tested in real industrial environments; the models involved are presented and discussed in the paper.Peer ReviewedPostprint (author's final draft

    Parsing Occluded People by Flexible Compositions

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    This paper presents an approach to parsing humans when there is significant occlusion. We model humans using a graphical model which has a tree structure building on recent work [32, 6] and exploit the connectivity prior that, even in presence of occlusion, the visible nodes form a connected subtree of the graphical model. We call each connected subtree a flexible composition of object parts. This involves a novel method for learning occlusion cues. During inference we need to search over a mixture of different flexible models. By exploiting part sharing, we show that this inference can be done extremely efficiently requiring only twice as many computations as searching for the entire object (i.e., not modeling occlusion). We evaluate our model on the standard benchmarked "We Are Family" Stickmen dataset and obtain significant performance improvements over the best alternative algorithms.Comment: CVPR 15 Camera Read

    The visual preferences for forest regeneration and field afforestation : four case studies in Finland

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    The overall aim of this dissertation was to study the public's preferences for forest regeneration fellings and field afforestations, as well as to find out the relations of these preferences to landscape management instructions, to ecological healthiness, and to the contemporary theories for predicting landscape preferences. This dissertation includes four case studies in Finland, each based on the visualization of management options and surveys. Guidelines for improving the visual quality of forest regeneration and field afforestation are given based on the case studies. The results show that forest regeneration can be connected to positive images and memories when the regeneration area is small and some time has passed since the felling. Preferences may not depend only on the management alternative itself but also on the viewing distance, viewing point, and the scene in which the management options are implemented. The current Finnish forest landscape management guidelines as well as the ecological healthiness of the studied options are to a large extent compatible with the public's preferences. However, there are some discrepancies. For example, the landscape management instructions as well as ecological hypotheses suggest that the retention trees need to be left in groups, whereas people usually prefer individually located retention trees to those trees in groups. Information and psycho-evolutionary theories provide some possible explanations for people's preferences for forest regeneration and field afforestation, but the results cannot be consistently explained by these theories. The preferences of the different stakeholder groups were very similar. However, the preference ratings of the groups that make their living from forest - forest owners and forest professionals - slightly differed from those of the others. These results provide support for the assumptions that preferences are largely consistent at least within one nation, but that knowledge and a reference group may also influence preferences.VÀitöskirjassa tutkittiin ihmisten maisemapreferenssejÀ (maisemallisia arvostuksia) metsÀnuudistamishakkuiden ja pellonmetsitysten suhteen sekÀ analysoitiin nÀiden preferenssien yhteyksiÀ maisemanhoito-ohjeisiin, vaihtoehtojen ekologiseen terveyteen ja preferenssejÀ ennustaviin teorioihin. VÀitöskirja sisÀltÀÀ neljÀ tapaustutkimusta, jotka perustuvat hoitovaihtoehtojen visualisointiin ja kyselytutkimuksiin. Tapaustutkimusten pohjalta annetaan ohjeita siitÀ, kuinka uudistushakkuiden ja pellonmetsitysten visuaalista laatua voidaan parantaa. VÀitöskirjan tulokset osoittavat, ettÀ uudistamishakkuut voivat herÀttÀÀ myös myönteisiÀ mielikuvia ja muistoja, jos uudistusala on pieni ja hakkuun vÀlittömÀt jÀljet ovat jo peittyneet. Preferensseihin vaikuttaa hoitovaihtoehdon lisÀksi mm. katseluetÀisyys, katselupiste ja ympÀristö, jossa vaihtoehto on toteutettu. Eri viiteryhmien (metsÀammattilaiset, pÀÀkaupunkiseudun asukkaat, ympÀristönsuojelijat, tutkimusalueiden matkailijat, paikalliset asukkaat sekÀ metsÀnomistajat) maisemapreferenssit olivat hyvin samankaltaisia. Kuitenkin ne ryhmÀt, jotka saavat ainakin osan elannostaan metsÀstÀ - metsÀnomistajat ja metsÀammattilaiset - pitivÀt metsÀnhakkuita esittÀvistÀ kuvista hieman enemmÀn kuin muut ryhmÀt. NÀmÀ tulokset tukevat oletusta, ettÀ maisemapreferenssit ovat laajalti yhtenevÀisiÀ ainakin yhden kansan tai kulttuurin keskuudessa, vaikka myös viiteryhmÀ saattaa vaikuttaa preferensseihin jonkin verran. Nykyiset metsÀmaisemanhoito-ohjeet ovat pitkÀlti samankaltaisia tÀssÀ vÀitöskirjassa havaittujen maisemapreferenssien kanssa. MyöskÀÀn tutkittujen vaihtoehtoisten hoitotapojen ekologisen paremmuuden ja niihin kohdistuvien maisemallisten arvostusten vÀlillÀ ei ollut suurta ristiriitaa. Kuitenkin joitakin eroavaisuuksia oli; esimerkiksi sekÀ maisemanhoito-ohjeiden ettÀ ekologisten hypoteesien mukaan sÀÀstöpuut tulisi jÀttÀÀ ryhmiin, kun taas ihmiset pitivÀt eniten yksittÀin jÀtetyistÀ puista. Informaatiomalli ja psyko-evolutionaarinen teoria tarjoavat mahdollisia selityksiÀ uudistushakkuisiin ja pellonmetsitykseen kohdistuville preferensseille, vaikkakaan tutkimuksen tuloksia ei voida tÀysin selittÀÀ nÀillÀ teorioilla

    Recurrent Human Pose Estimation

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    We propose a novel ConvNet model for predicting 2D human body poses in an image. The model regresses a heatmap representation for each body keypoint, and is able to learn and represent both the part appearances and the context of the part configuration. We make the following three contributions: (i) an architecture combining a feed forward module with a recurrent module, where the recurrent module can be run iteratively to improve the performance, (ii) the model can be trained end-to-end and from scratch, with auxiliary losses incorporated to improve performance, (iii) we investigate whether keypoint visibility can also be predicted. The model is evaluated on two benchmark datasets. The result is a simple architecture that achieves performance on par with the state of the art, but without the complexity of a graphical model stage (or layers).Comment: FG 2017, More Info and Demo: http://www.robots.ox.ac.uk/~vgg/software/keypoint_detection

    No-reference bitstream-based visual quality impairment detection for high definition H.264/AVC encoded video sequences

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    Ensuring and maintaining adequate Quality of Experience towards end-users are key objectives for video service providers, not only for increasing customer satisfaction but also as service differentiator. However, in the case of High Definition video streaming over IP-based networks, network impairments such as packet loss can severely degrade the perceived visual quality. Several standard organizations have established a minimum set of performance objectives which should be achieved for obtaining satisfactory quality. Therefore, video service providers should continuously monitor the network and the quality of the received video streams in order to detect visual degradations. Objective video quality metrics enable automatic measurement of perceived quality. Unfortunately, the most reliable metrics require access to both the original and the received video streams which makes them inappropriate for real-time monitoring. In this article, we present a novel no-reference bitstream-based visual quality impairment detector which enables real-time detection of visual degradations caused by network impairments. By only incorporating information extracted from the encoded bitstream, network impairments are classified as visible or invisible to the end-user. Our results show that impairment visibility can be classified with a high accuracy which enables real-time validation of the existing performance objectives
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