logo EDITE Nicolas BOURDIS
Identité
Nicolas BOURDIS
État académique
Thèse soutenue le 2013-05-24
Sujet: Exploitation de vidéos aériennes multiples pour la détection de changements
Direction de thèse:
Laboratoire:
Voisinage
Ellipse bleue: doctorant, ellipse jaune: docteur, rectangle vert: permanent, rectangle jaune: HDR. Trait vert: encadrant de thèse, trait bleu: directeur de thèse, pointillé: jury d'évaluation à mi-parcours ou jury de thèse.
Productions scientifiques
oai:hal.archives-ouvertes.fr:hal-00722250
SPATIO-TEMPORAL INTERACTION FOR AERIAL VIDEO CHANGE DETECTION
With the growing capacity of video devices, human operators are nowadays overwhelmed by the huge volumes of data generated in different applications including surveillance. Therefore, automatic video processing techniques are required in order to filter out uninteresting data and to focus the attention of operators. However, reliability is still a challenging problem. In this paper, we show how spatio-temporal redundancy may be exploited to enhance the accuracy of automatic change detection in aerial videos. More precisely, we present an algorithm based on Belief Propagation in order to improve spatio-temporal consistency between successive change detection results. Experiments demonstrate that our method leads to increased accuracy in change detection.
Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)proceeding with peer review 2012
oai:hal.archives-ouvertes.fr:hal-00722249
CAMERA POSE ESTIMATION USING VISUAL SERVOING FOR AERIAL VIDEO CHANGE DETECTION
Aerial image change detection is highly dependent on the accuracy of camera pose and may be subject to false alarms caused by mis-registrations. In this paper, we present a novel pose estimation approach based on Visual Servoing that combines aerial videos with 3D models. Firstly, we introduce a formulation that relates image registration with the poses of a moving camera observing a 3D plane. Then, we combine this formulation with Newton's algorithm in order to estimate camera poses in a given aerial video. Finally, we present and discuss experimental results which demonstrate the robustness and the accuracy of our method.
Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2012 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)proceeding with peer review 2012
oai:hal.archives-ouvertes.fr:hal-00667237
Constrained optical flow for aerial image change detection
Nowadays, the amount of video data acquired for observation or surveillance applications is overwhelming. Due to these huge volumes of video data, focusing the attention of operators on "areas of interest" requires change detection algorithms. In the particular task of aerial observation, camera motion and viewpoint differences introduce parallax effects, which may substantially affect the reliability and the efficiency of automatic change detection. In this paper, we introduce a novel approach for change detection that considers the geometric aspects of camera sensors as well as the statistical properties of changes. Indeed, our method is based on optical flow matching, constrained by the epipolar geometry, and combined with a statistical change decision criterion. The good performance of our method is demonstrated through our new public Aerial Imagery Change Detection (AICD) dataset of labeled aerial images.
Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2011 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)proceeding with peer review 2011
Soutenance
Thèse: Détection de changements entre vidéos aériennes avec trajectoires arbitraires
Soutenance: 2013-05-24