Pointless Global Bundle Adjustment With Relative Motions Hessians

Bundle adjustment (BA) is the standard way to optimise camera poses and to produce sparse representations of a scene. However, as the number of camera poses and features grows, refinement through bundle adjustment becomes inefficient. Inspired by global motion averaging methods, we propose a new bundle adjustment objective which does not rely on image features' reprojection errors yet maintains precision on par with classical BA. Our method averages over relative motions while implicitly incorporating the contribution of the structure in the adjustment. To that end, we weight the objective function by local hessian matrices - a by-product of local bundle adjustments performed on relative motions (e.g., pairs or triplets) during the pose initialisation step. Such hessians are extremely rich as they encapsulate both the features' random errors and the geometric configuration between the cameras. These pieces of information propagated to the global frame help to guide the final optimisation in a more rigorous way. We argue that this approach is an upgraded version of the motion averaging approach and demonstrate its effectiveness on both photogrammetric datasets and computer vision benchmarks

DSM GENERATION FROM STEREOSCOPIC IMAGERY FOR DAMAGE MAPPING, APPLICATION ON THE TOHOKU TSUNAMI

International audienceChange detection methods from remote sensing are largely investigated, especially for damage mapping after a disaster such as tsunami, earthquake, flood or landslide. In this context, a fast evaluation and localization of the inferred damages is essential for the rescue teams and the authorities [1], [2], [3], an automatic method is then particularly adapted. Today, most of the automatic or semi-automatic change detection methods are based on radiometric changes [2] but a significant amount these changes are irrelevant. An alternative is a change detection method involving objects elevation [4]. The advantage of using this information is that most of the indexed changes are of interest, especially in an urban context. A previously submitted article describes the fully automatic and generic processing flow we developed for the production of change detection maps from stereoscopic images. This flow consists in the generation of accurate Digital Surface Model (DSM) with an improved image-space based matching technique followed by the detection of real changes from the DSM difference through a classification method with a spatial regularization constraint. In this article, we present the application of this methodology on a real application case, the 2011 earthquake and tsunami occurred on the Tohoku region, in Japan

Détection des changements d'élévation d'une scène par imagerie satellite stéréoscopique

Session "Posters"National audienceCet article propose une méthode de détection de changements à partir de couples d'images stéréoscopiques très haute résolution. Le but est de mettre en évidence, sur une image labellisée, les changements altimétriques apparus entre deux scènes. Cette méthode s'appui sur une spatio-triangulation par l'affinage simultané des modèles géométriques de toutes les images de l'étude. Pour les capteurs présentant des défauts de modélisation géométrique, la mise en correspondance des images de chaque couple est effectuée grâce à une recherche bidimensionnelle dans l'espace terrain et image. Les Modèles Numériques de Surface (MNS) issus de chaque couple et comparables à l'échelle du pixel sont soustraits et une classification non supervisée est appliquée à la carte de différence à l'aide d'une régularisation spatiale. Cette technique permet de réduire les fausses alarmes dues au bruit de corrélation tout en gardant une très bonne détection des changements pertinents. Sur les zones testées, on atteint l'objectif de plus de 90% de vrais changements détectés avec un taux de fausses alarmes permettant un gain de temps significatif par rapport à une inspection humaine exhaustiv

Ocular Motor Apraxia after Sequential Bilateral Striatal Infarctions

Ocular motor apraxia has been reported in bilateral frontoparietal lesions. We report a case of ocular motor apraxia after bilateral striatal infarctions. The patient had impaired voluntary saccades and smooth pursuits in the vertical and horizontal planes with an intact vestibulo-ocular reflex. Magnetic resonance imaging showed an old left putaminal infarction and an acute infarction in the right caudoputaminal area. This case demonstrates that ocular motor apraxia may occur in bilateral basal ganglia lesions

Presumed Metastasis of Breast Cancer to the Abducens Nucleus Presenting as Gaze Palsy

A 51-year-old woman with breast cancer presented with progressive diplopia. Neuro-ophthalmologic examination revealed right gaze palsy and peripheral facial nerve palsy. Brain magnetic resonance imaging (MRI) was normal. However, two months later a repeat brain MRI revealed an enhancing round nodular mass at the right facial colliculus of the lower pons, at the location of the abducens nucleus. Localized metastasis to the abducens nucleus can cause gaze palsy in a patient with breast cancer

Traitement de données lidar à retour d'onde complète pour l'extraction de paramètres forestiers et de modèle numérique de terrain : validataion en forêt de conifères dans les Alpes

International audienceSmall footprint discrete return lidar data have already proved useful for providing information on forest areas. During the last decade, a new generation of airborne laser scanners, called full-waveform (FW) lidar systems, has emerged. They digitize and record the entire backscattered signal of each emitted pulse. Fullwaveform data hold large potentialities. In this study, we investigated the processing of raw full-waveform lidar data for deriving Digital Terrain Model (DTM) and Canopy Height Model (CHM). The main objective of this work was to compare geometric information derived from full-waveform and multi-echo data for various stands. An enhanced peak detection algorithm developed in a previous study was used to extract target positions from full-waveform data on plots under different stand characteristics. The resulting 3D point clouds were compared to the discrete return lidar observations provided by the lidar operator. Ground points were then identified using an original classification algorithm. They were used to derive DTMs which were compared to ground truth. Digital Surface Models were obtained from first echoes and canopy height models were then computed. Detecting weak echoes, when processing full-waveform data, enabled to better describe the canopy shape and to penetrate deeper into forest cover. However DTM was not significantly improved

Traitement de données à retour d'onde complète : modélisation du signal brut

International audienceUnlike airborne multi-echo laser scanner systems, full-waveform systems are able to digitize and record the entire backscattered signal of each laser pulse. It has been demonstrated that decomposing the return waveforms into a mixture of Gaussian components was suitable. In this paper, we focus on the improvement of peak detection and of raw signal modelling. Refined peak detection greatly increased the number of detected targets as well as their positional accuracy. Models more complex than the Gaussian model, such as the Lognormal or generalized Gaussian functions, were introduced and their contribution to waveform processing was studied. In this way, fitting of asymmetric, peaked or flattened echoes located both in urban and forested areas could be improved. Moreover, introduction of new echo parameters allowed the extraction of additional information on the target shape. This should make easier the decorrelation of geometric and radiometric influences on the signal and, as a consequence, the improvement of point cloud classification algorithms

Information processing in long delay memory-guided saccades: further insights from TMS

The performance of memory-guided saccades with two different delays (3s and 30s of memorisation) was studied in eight subjects. Single pulse transcranial magnetic stimulation (TMS) was applied simultaneously over the left and right dorsolateral prefrontal cortex (DLPFC) 1s after target presentation. In both delays, stimulation significantly increased the percentage of error in amplitude of memory-guided saccades. Furthermore, the interfering effect of TMS was significantly higher in the short delay compared to that of the long delay paradigm. The results are discussed in the context of a mixed model of spatial working memory control including two components: First, serial information processing with a predominant role of the DLPFC during the early period of memorisation and, second, parallel information processing, which is independent from the DLPFC, operating during longer delay