Sensor-Assisted Video Mosaicing for Seafloor Mapping

This paper discusses a proposed processing technique for combining video imagery with auxiliary sensor information. The latter greatly simplifies image processing by reducing complexity of the transformation model. The mosaics produced by this technique are adequate for many applications, in particular habitat mapping. The algorithm is demonstrated through simulations and hardware configuration is described

Improvement of Image Alignment Using Camera Attitude Information

We discuss a proposed technique for incorporation of information from a variety of sensors in a video imagery processing pipeline. The auxiliary information allows one to simplify computations, effectively reducing the number of independent parameters in the transformation model. The mosaics produced by this technique are adequate for many applications, in particular habitat mapping. The algorithm, demonstrated through simulations and hardware configuration, is described in detai

Enhancement of Underwater Video Mosaics for Post-Processing

Mosaics of seafloor created from still images or video acquired underwater have proved to be useful for construction of maps of forensic and archeological sites, species\u27 abundance estimates, habitat characterization, etc. Images taken by a camera mounted on a stable platform are registered (at first pair-wise and then globally) and assembled in a high resolution visual map of the surveyed area. While this map is usually sufficient for a human orientation and even quantitative measurements, it often contains artifacts that complicate an automatic post-processing (for example, extraction of shapes for organism counting, or segmentation for habitat characterization). The most prominent artifacts are inter-frame seams caused by inhomogeneous artificial illumination, and local feature misalignments due to parallax effects - result of an attempt to represent a 3D world on a 2D map. In this paper we propose two image processing techniques for mosaic quality enhancement - median mosaic-based illumination correction suppressing appearance of inter-frame seams, and micro warping decreasing influence of parallax effects

Seafloor Video Mapping: Modeling, Algorithms, Apparatus

This paper discusses a technique used for construction of high-resolution image mosaic from a videosequence and the synchronously logged camera attitude information. It allows one to infer geometric characteristics of the imaged terrain and hence improve the mosaic quality and reduce the computational burden. The technique is demonstrated using numerical modeling and is applied to videodata collected on Rainsford Island, Mass. Calculation of the transformation relating consecutive image frames is an essential operation affecting reliability of the whole mosaicing process. Improvements to the algorithm are suggested, which significantly decrease the possibility of convergence to an inappropriate solution

Large Area 3D Reconstructions from Underwater Surveys

Robotic underwater vehicles can perform vast optical surveys of the ocean floor. Scientists value these surveys since optical images offer high levels of information and are easily interpreted by humans. Unfortunately the coverage of a single image is limited hy absorption and backscatter while what is needed is an overall view of the survey area. Recent work on underwater mosaics assume planar scenes and are applicable only to Situations without much relief. We present a complete and validated system for processing optical images acquired from an underwater mbotic vehicle to form a 3D reconstruction of the wean floor. Our approach is designed for the most general conditions of wide-baseline imagery (low overlap and presence of significant 3D structure) and scales to hundreds of images. We only assume a calibrated camera system and a vehicle with uncertain and possibly drifting pose information (e.g. a compass, depth sensor and a Doppler velocity Our approach is based on a combination of techniques from computer vision, photogrammetry and mhotics. We use a local to global approach to structure from motion, aided by the navigation sensors on the vehicle to generate 3D suhmaps. These suhmaps are then placed in a common reference frame that is refined by matching overlapping submaps. The final stage of processing is a bundle adjustment that provides the 3D structure, camera poses and uncertainty estimates in a consistent reference frame. We present results with ground-truth for structure as well as results from an oceanographic survey over a coral reef covering an area of appmximately one hundred square meters.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86037/1/opizarro-33.pd

Improving Sonar Image Patch Matching via Deep Learning

Matching sonar images with high accuracy has been a problem for a long time, as sonar images are inherently hard to model due to reflections, noise and viewpoint dependence. Autonomous Underwater Vehicles require good sonar image matching capabilities for tasks such as tracking, simultaneous localization and mapping (SLAM) and some cases of object detection/recognition. We propose the use of Convolutional Neural Networks (CNN) to learn a matching function that can be trained from labeled sonar data, after pre-processing to generate matching and non-matching pairs. In a dataset of 39K training pairs, we obtain 0.91 Area under the ROC Curve (AUC) for a CNN that outputs a binary classification matching decision, and 0.89 AUC for another CNN that outputs a matching score. In comparison, classical keypoint matching methods like SIFT, SURF, ORB and AKAZE obtain AUC 0.61 to 0.68. Alternative learning methods obtain similar results, with a Random Forest Classifier obtaining AUC 0.79, and a Support Vector Machine resulting in AUC 0.66.Comment: Author versio

Large Area 3-D Reconstructions from Underwater Optical Surveys

Robotic underwater vehicles are regularly performing vast optical surveys of the ocean floor. Scientists value these surveys since optical images offer high levels of detail and are easily interpreted by humans. Unfortunately, the coverage of a single image is limited by absorption and backscatter while what is generally desired is an overall view of the survey area. Recent works on underwater mosaics assume planar scenes and are applicable only to situations without much relief. We present a complete and validated system for processing optical images acquired from an underwater robotic vehicle to form a 3D reconstruction of the ocean floor. Our approach is designed for the most general conditions of wide-baseline imagery (low overlap and presence of significant 3D structure) and scales to hundreds or thousands of images. We only assume a calibrated camera system and a vehicle with uncertain and possibly drifting pose information (e.g., a compass, depth sensor, and a Doppler velocity log). Our approach is based on a combination of techniques from computer vision, photogrammetry, and robotics. We use a local to global approach to structure from motion, aided by the navigation sensors on the vehicle to generate 3D sub-maps. These sub-maps are then placed in a common reference frame that is refined by matching overlapping sub-maps. The final stage of processing is a bundle adjustment that provides the 3D structure, camera poses, and uncertainty estimates in a consistent reference frame. We present results with ground truth for structure as well as results from an oceanographic survey over a coral reef.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86036/1/opizarro-12.pd

Visually pleasant blending techniques in underwater mosaicing

of two or more images that are then combined into a single and usually larger one. The applications of mosaicing comprehend panoramic photography, super-resolution, virtual environments and vision based navigation systems, as a most relevant exponents. Besides generic camera issues as geometric and chromatic distortions, underwa-ter images are aff ected by particular factors as non-uniform illumination, caustics, blurring, suspended particles and scattering, making even more diffi cult the alignment and blend-ing. The aim of this work is to perform a re-view on the existing image blending techniques specially focusing the study on its application on the underwater imaging

Mosaicing Tool for Aerial Imagery from a Lidar Bathymetry Survey

Aerial imagery collected during lidar bathymetry surveying provides an independent reference dataset for ground truth. Mosaicing of aerial imagery requires some manual involvement by the operator, which is time consuming. This paper presents an automatic mosaicing procedure that creates a continuous and visually consistent photographic map of the imaged area. This study aimed to use only the frames from the aerial camera without additional information. A comparison between the features in the resultant mosaic and a reference chart shows that the mosaic is visually consistent and there is good spatial-geometric correlation of features.Las imagenes aereas recogidas durante los levantamientos batimetricos efectuados con el lfdar proporcionan una coleccion de datos de referencia independientes para la validacion en el terreno. La composicion de las imagenes aereas en forma de mosaico requiere una cierta implicacion manual par parte del operador, to que toma mucho tiempo. Este articulo presenta un procedimiento para la composicion automatica en forma de mosaico, que crea un mapa fotografico continuo y visuatmente coherente de la zona representada en la imagen. El objetivo de este estudio es utilizar solo los marcos de la camara aerea sin informacion adicional. Una comparacion entre las caracterfsticas del mosaico resultante y una carta de referencia muestra que el mosaico es visualmente coherente y que hay una buena correlacion geometrico-espacial de las caracteristicas.L'imagerie aerienne effectuee pendant les leves bathymetriques lidar constitue un ensemble de donnees de reference independant, pour la realite de terrain. Le mosaiiquage de l'imagerie aerienne requiert une intervention manuelle de l'operateur, laquelle prend beaucoup de temps. Cet article presente une procedure de mosaiiquage automatique qui permet d'obtenir une carte photographique continue et visuellement coherente de la zone couverte. L'objectif de cette etude consiste a utiliser seulement les images de la camera aerienne sans informations supptementaires. Une comparaison entre tes elements dans la mosaique resultante et une carte de reference montre que la mosaique est visuellement coherente et qu'il existe une bonne correlation geometrique-spatiale des elements

Mosaicing Tool for Aerial Imagery from a Lidar Bathymetry Survey

Aerial imagery collected during lidar bathymetry surveying provides an independent reference dataset for ground truth. Mosaicing of aerial imagery requires some manual involvement by the operator, which is time consuming. This paper presents an automatic mosaicing procedure that creates a continuous and visually consistent photographic map of the imaged area. This study aimed to use only the frames from the aerial camera without additional information. A comparison between the features in the resultant mosaic and a reference chart shows that the mosaic is visually consistent and there is good spatial-geometric correlation of features.Las imagenes aereas recogidas durante los levantamientos batimetricos efectuados con el lfdar proporcionan una coleccion de datos de referencia independientes para la validacion en el terreno. La composicion de las imagenes aereas en forma de mosaico requiere una cierta implicacion manual par parte del operador, to que toma mucho tiempo. Este articulo presenta un procedimiento para la composicion automatica en forma de mosaico, que crea un mapa fotografico continuo y visuatmente coherente de la zona representada en la imagen. El objetivo de este estudio es utilizar solo los marcos de la camara aerea sin informacion adicional. Una comparacion entre las caracterfsticas del mosaico resultante y una carta de referencia muestra que el mosaico es visualmente coherente y que hay una buena correlacion geometrico-espacial de las caracteristicas.L'imagerie aerienne effectuee pendant les leves bathymetriques lidar constitue un ensemble de donnees de reference independant, pour la realite de terrain. Le mosaiiquage de l'imagerie aerienne requiert une intervention manuelle de l'operateur, laquelle prend beaucoup de temps. Cet article presente une procedure de mosaiiquage automatique qui permet d'obtenir une carte photographique continue et visuellement coherente de la zone couverte. L'objectif de cette etude consiste a utiliser seulement les images de la camera aerienne sans informations supptementaires. Une comparaison entre tes elements dans la mosaique resultante et une carte de reference montre que la mosaique est visuellement coherente et qu'il existe une bonne correlation geometrique-spatiale des elements