Foix Salmeron, Sergi
Total activity: 9
Research group
ROBiri - IRI Robotics Group
Institute
Institute of Robotics and Industrial Informatics
E-mail
sergi.foixestudiant.upc.edu
Contact details
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Scientific and technological production
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1 to 9 of 9 results
  • Robotic leaf probing via segmentation of range data into surface patches

     Alenyà Ribas, Guillem; Dellen, Babette Karla Margarete; Foix Salmeron, Sergi; Torras, Carme
    IROS Workshop on Agricultural Robotics: Enabling Safe, Efficient, Affordable Robots for Food Production (IROS AGROBOTICS)
    Presentation's date: 2012
    Presentation of work at congresses

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    Plant leaf imaging using time of flight camera under sunlight, shadow and room conditions  Open access

     Kazmi, Wajahat; Alenyà Ribas, Guillem; Foix Salmeron, Sergi
    IEEE International Symposium on Robotic and Sensors Environments
    Presentation's date: 2012
    Presentation of work at congresses

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    In this article, we analyze the effects of ambient light on Time of Flight (ToF) depth imaging for a plant’s leaf in sunlight, shadow and room conditions. ToF imaging is sensitive to ambient light and we try to find the best possible integration times (IT) for each condition. This is important in order to optimize camera calibration. Our analysis is based on several statistical metrics estimated from the ToF data. We explain the estimation of the metrics and propose a method of predicting the deteriorating behavior of the data in each condition using camera flags. Finally, we also propose a method to improve the quality of a ToF image taken in a mixed condition having different ambient light exposures.

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    Information-gain view planning for free-form object reconstruction with a 3D ToF camera  Open access

     Foix Salmeron, Sergi; Kriegel, Simon; Fuchs, Stefan; Alenyà Ribas, Guillem; Torras, Carme
    International Conference on Advanced Concepts for Intelligent Vision Systems
    Presentation's date: 2012
    Presentation of work at congresses

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    Active view planning for gathering data from an unexplored 3D complex scenario is a hard and still open problem in the computer vision community. In this paper, we present a general task-oriented approach based on an information-gain maximization that easily deals with such a problem. Our approach consists of ranking a given set of possible actions, based on their task-related gains, and then executing the best-ranked action to move the required sensor. An example of how our approach behaves is demonstrated by applying it over 3D raw data for real-time volume modelling of complex-shaped objects. Our setting includes a calibrated 3D time-of-flight (ToF) camera mounted on a 7 degrees of freedom (DoF) robotic arm. Noise in the sensor data acquisition, which is too often ignored, is here explicitly taken into account by computing an uncertainty matrix for each point, and refining this matrix each time the point is seen again. Results show that, by always choosing the most informative view, a complete model of a 3D free-form object is acquired and also that our method achieves a good compromise between speed and precision.

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    Segmenting color images into surface patches by exploiting sparse depth data  Open access

     Dellen, Babette Karla Margarete; Alenyà Ribas, Guillem; Foix Salmeron, Sergi; Torras, Carme
    Winter Vision Meeting: Workshop on Applications of Computer Vision
    Presentation's date: 2011
    Presentation of work at congresses

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    We present a new method for segmenting color images into their composite surfaces by combining color segmentation with model-based fitting utilizing sparse depth data, acquired using time-of-flight (Swissranger, PMD CamCube) and stereo techniques. The main target of our work is the segmentation of plant structures, i.e., leaves, from color-depth images, and the extraction of color and 3D shape information for automating manipulation tasks. Since segmentation is performed in the dense color space, even sparse, incomplete, or noisy depth information can be used. This kind of data often represents a major challenge for methods operating in the 3D data space directly. To achieve our goal, we construct a three-stage segmentation hierarchy by segmenting the color image with different resolutions-assuming that “true” surface boundaries must appear at some point along the segmentation hierarchy. 3D surfaces are then fitted to the color-segment areas using depth data. Those segments which minimize the fitting error are selected and used to construct a new segmentation. Then, an additional region merging and a growing stage are applied to avoid over-segmentation and label previously unclustered points. Experimental results demonstrate that the method is successful in segmenting a variety of domestic objects and plants into quadratic surfaces. At the end of the procedure, the sparse depth data is completed using the extracted surface models, resulting in dense depth maps. For stereo, the resulting disparity maps are compared with ground truth and the average error is computed.

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    Towards plant monitoring through next best view  Open access

     Foix Salmeron, Sergi; Alenyà Ribas, Guillem; Torras, Carme
    International Conference of the Catalan Association for Artificial Intelligence
    Presentation's date: 2011
    Presentation of work at congresses

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    Monitoring plants using leaf feature detection is a challenging perception task because different leaves, even from the same plant, may have very different shapes, sizes and deformations. In addition, leaves may be occluded by other leaves making it hard to determine some of their characteristics. In this paper we use a Time-of-Flight (ToF) camera mounted on a robot arm to acquire the depth information needed for plant leaf detection. Under a Next Best View (NBV) paradigm, we propose a criterion to compute a new camera position that offers a better view of a target leaf. The proposed criterion exploits some typical errors of the ToF camera, which are common to other 3D sensing devices as well. This approach is also useful when more than one leaf is segmented as the same region, since moving the camera following the same NBV criterion helps to disambiguate this situation.

    Postprint (author’s final draft)

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    Lock-in time-of-flight (ToF) cameras: a survey  Open access

     Foix Salmeron, Sergi; Alenyà Ribas, Guillem; Torras, Carme
    IEEE sensors journal
    Date of publication: 2011
    Journal article

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    This paper reviews the state-of-the art in the field of lock-in ToF cameras, their advantages, their limitations, the existing calibration methods, and the way they are being used, sometimes in combination with other sensors. Even though lockin ToF cameras provide neither higher resolution nor larger ambiguity-free range compared to other range map estimation systems, advantages such as registered depth and intensity data at a high frame rate, compact design, low weight and reduced power consumption have motivated their increasing usage in several research areas, such as computer graphics, machine vision and robotics.

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    Object modeling using a ToF camera under an uncertainty reduction approach  Open access

     Foix Salmeron, Sergi; Alenyà Ribas, Guillem; Andrade Cetto, Juan; Torras, Carme
    IEEE International Conference on Robotics and Automation
    Presentation's date: 2010
    Presentation of work at congresses

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    Time-of-Flight (ToF) cameras deliver 3D images at 25 fps, offering great potential for developing fast object modeling algorithms. Surprisingly, this potential has not been extensively exploited up to now. A reason for this is that, since the acquired depth images are noisy, most of the available registration algorithms are hardly applicable. A further difficulty is that the transformations between views are in general not accurately known, a circumstance that multi-view object modeling algorithms do not handle properly under noisy conditions. In this work, we take into account both uncertainty sources (in images and camera poses) to generate spatially consistent 3D object models fusing multiple views with a probabilistic approach. We propose a method to compute the covariance of the registration process, and apply an iterative state estimation method to build object models under noisy conditions.

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    Exploitation of time-of-flight (ToF) cameras  Open access

     Foix Salmeron, Sergi; Alenyà Ribas, Guillem; Torras, Carme
    Date: 2010
    Report

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    This technical report reviews the state-of-the art in the field of ToF cameras, their advantages, their limitations, and their present-day applications sometimes in combination with other sensors. Even though ToF cameras provide neither higher resolution nor larger ambiguity-free range compared to other range map estimation systems, advantages such as registered depth and intensity data at a high frame rate, compact design, low weight and reduced power consumption have motivated their use in numerous areas of research. In robotics, these areas range from mobile robot navigation and map building to vision-based human motion capture and gesture recognition, showing particularly a great potential in object modeling and recognition.

  • 3D object reconstruction from Swissranger sensor data using a spring-mass model

     Dellen, Babette Karla Margarete; Alenyà Ribas, Guillem; Foix Salmeron, Sergi; Torras, Carme
    Date of publication: 2009
    Book chapter

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