Learning to Segment Moving Objects in Videos

We segment moving objects in videos by ranking spatio-temporal segment proposals according to "moving objectness": how likely they are to contain a moving object. In each video frame, we compute segment proposals using multiple figure-ground segmentations on per frame motion boundaries. We rank them with a Moving Objectness Detector trained on image and motion fields to detect moving objects and discard over/under segmentations or background parts of the scene. We extend the top ranked segments into spatio-temporal tubes using random walkers on motion affinities of dense point trajectories. Our final tube ranking consistently outperforms previous segmentation methods in the two largest video segmentation benchmarks currently available, for any number of proposals. Further, our per frame moving object proposals increase the detection rate up to 7\% over previous state-of-the-art static proposal methods

Optimal and fast rotational alignment of volumes with missing data in Fourier space

AbstractElectron tomography of intact cells has the potential to reveal the entire cellular content at a resolution corresponding to individual macromolecular complexes. Characterization of macromolecular complexes in tomograms is nevertheless an extremely challenging task due to the high level of noise, and due to the limited tilt angle that results in missing data in Fourier space. By identifying particles of the same type and averaging their 3D volumes, it is possible to obtain a structure at a more useful resolution for biological interpretation. Currently, classification and averaging of sub-tomograms is limited by the speed of computational methods that optimize alignment between two sub-tomographic volumes. The alignment optimization is hampered by the fact that the missing data in Fourier space has to be taken into account during the rotational search. A similar problem appears in single particle electron microscopy where the random conical tilt procedure may require averaging of volumes with a missing cone in Fourier space. We present a fast implementation of a method guaranteed to find an optimal rotational alignment that maximizes the constrained cross-correlation function (cCCF) computed over the actual overlap of data in Fourier space

Multiscale combinatorial grouping for image segmentation and object proposal generation

We propose a unified approach for bottom-up hierarchical image segmentation and object proposal generation for recognition, called Multiscale Combinatorial Grouping (MCG). For this purpose, we first develop a fast normalized cuts algorithm. We then propose a high-performance hierarchical segmenter that makes effective use of multiscale information. Finally, we propose a grouping strategy that combines our multiscale regions into highly-accurate object proposals by exploring efficiently their combinatorial space. We also present Single-scale Combinatorial Grouping (SCG), a faster version of MCG that produces competitive proposals in under five seconds per image. We conduct an extensive and comprehensive empirical validation on the BSDS500, SegVOC12, SBD, and COCO datasets, showing that MCG produces state-of-the-art contours, hierarchical regions, and object proposals.Peer ReviewedPostprint (author's final draft

Diseño de un sistema productivo sustentable para producción de panela en el municipio de Nariño, Antioquia

Colombia es un país reconocido por la producción de panela a nivel mundial, pero con inconvenientes en sus métodos de realización del producto, por ser muy artesanales en varios lugares del territorio. Esto motivó a realizar este estudio para un diseño de un sistema productivo sustentable de panela en el Municipio de Nariño, Antioquia por su tradición en la elaboración de este tipo de productos. El diseño se elabora a partir de diagramaciones que muestren las actividades del proceso y determinando la tecnología que se desea implementar, siendo un punto decisivo en la manera de producción de la panela; por último, se hace la distribución más pertinente en los centros de trabajo, teniendo en cuenta las medidas en las áreas de los diversos lugares de producción y que sirva finalmente como base para las personas de la región que deseen emprender en la producción de panela, una forma amigable con el ambienteColombia is a country recognized for the production of panela worldwide, but with drawbacks in its methods of making the product, for being very traditional in various parts of the territory. This motivated to carry out this study for a design of a sustainable panela production system in the Municipality of Nariño, Antioquia due to its tradition in the elaboration of this type of products. The design is made from diagrams that show the activities of the process and determining the technology to be implemented, being a decisive point in the way of production of the panela; Finally, the most pertinent distribution is made in the work centers, taking into account the measures in the areas of the various places of production and that finally serves as a base for the people of the region who wish to undertake the production of panela, an environmentally friendly wayRionegr