Visual vocabularies for category-level object recognition

This thesis focuses on the study of visual vocabularies for category-level object recognition. Specifically, we state novel approaches for building visual codebooks. Our aim is not just to obtain more discriminative and more compact visual codebooks, but to bridge the gap between visual features and semantic concepts. A novel approach for obtaining class representative visual words is presented. It is based on a maximisation procedure, i. e. the Cluster Precision Maximisation (CPM), of a novel cluster precision criterion, and on an adaptive threshold refinement scheme for agglomerative clustering algorithms based on correlation clustering techniques. The objective is to increase the vocabulary compactness while at the same time improve the recognition rate and further increase the representativeness of the visual words. Moreover, we describe a novel clustering aggregation based approach for building efficient and semantic visual vocabularies. It consist of a novel framework for incorporating neighboring appearances of local descriptors into the vocabulary construction, and a rigorous approach for adding meaningful spatial coherency among the local features into the visual codebooks. We also propose an efficient high-dimensional data clustering algorithm, the Fast Reciprocal Nearest Neighbours (Fast-RNN). Our approach, which is a speeded up version of the standard RNN algorithm, is based on the projection search paradigm. Finally, we release a new database of images called Image Collection of Annotated Real-world Objects (ICARO), which is especially designed for evaluating category-level object recognition systems. An exhaustive comparison of ICARO with other well-known datasets used within the same context is carried out. We also propose a benchmark for both object classification and detection

Visual vocabularies for category-level object recognition

This thesis focuses on the study of visual vocabularies for category-level object recognition. Specifically, we state novel approaches for building visual codebooks. Our aim is not just to obtain more discriminative and more compact visual codebooks, but to bridge the gap between visual features and semantic concepts. A novel approach for obtaining class representative visual words is presented. It is based on a maximisation procedure, i. e. the Cluster Precision Maximisation (CPM), of a novel cluster precision criterion, and on an adaptive threshold refinement scheme for agglomerative clustering algorithms based on correlation clustering techniques. The objective is to increase the vocabulary compactness while at the same time improve the recognition rate and further increase the representativeness of the visual words. Moreover, we describe a novel clustering aggregation based approach for building efficient and semantic visual vocabularies. It consist of a novel framework for incorporating neighboring appearances of local descriptors into the vocabulary construction, and a rigorous approach for adding meaningful spatial coherency among the local features into the visual codebooks. We also propose an efficient high-dimensional data clustering algorithm, the Fast Reciprocal Nearest Neighbours (Fast-RNN). Our approach, which is a speeded up version of the standard RNN algorithm, is based on the projection search paradigm. Finally, we release a new database of images called Image Collection of Annotated Real-world Objects (ICARO), which is especially designed for evaluating category-level object recognition systems. An exhaustive comparison of ICARO with other well-known datasets used within the same context is carried out. We also propose a benchmark for both object classification and detection

Neurofibroma plexiforme en mucosa yugal: presentación de un caso clínico

Presentamos un caso clínico de neurofibroma plexiforme localizado en región geniana, a nivel submucoso. Su interés radica en que, a pesar de ser el tumor de origen neurógeno más frecuente, es una entidad poco habitual y que rara vez se localiza a nivel intraoral. Por otra parte, la variedad plexiforme es todavía menos frecuente. Desde el punto de vista clínico, se manifiestan como lesiones anodinas, con escasa sintomatología, que cuando aparece es derivada de la compresión nerviosa. En nuestro caso el tumor era asintomático salvo por el tamaño. Radiológicamente no existe una imagen definitiva. Tiene relación con determinados síndromes poliglandulares y facomatosis. El tratamiento es básicamente quirúrgico aunque existen dudas de la idoneidad del mismo y se están buscando nuevas vías de tratamiento. Aprovechando la descripción del caso se realiza una revisión bibliográfica incidiendo en la epidemiología, comportamiento clínico, métodos diagnósticos, así como en el tratamiento de este tipo de tumores benignos.The case reported deals with a solitary plexiform neurofibroma affecting the cheek submucosa. Neurofibroma is an uncommon tumor which rarely appears in oral cavity but it represents the most common neurogenic tumor. Furthermore, plexiform variety is less frequent. Clinically, oral neurofibromas usually apperars as anodyne and asintomatic lesions. Sometimes, they produce nervous compression. In this case, tumor is big but asintomatic. There is no definitive radiologic image. It has association with poliglandular syndroms and phacomatosis. The treatment of choice is excision. There are doubts of the surgical results so that some authors are looking for new non-surgical treatments. The clinical characteristics, epidemiology, diagnosis and treatment are described as soon as a bibliographic revision

Road Sign Analysis Using Multisensory Data

This paper deals with the problem of estimating the following road sign parameters: height, dimensions, visibility distance and partial occlusions. This work belongs to a framework whose main applications involve road sign maintenance, driver assistance, and inventory systems. From this paper we suggest a multisensory system composed from two cameras, a GPS receiver, and a distance measurement device,all of them installed in a car. The process consists of several steps which include road sign detection, recognition and tracking , and road signs parameters estimation. From some trigonometric properties, and a camera model, the information provided by the tracking subsystem and the distance measurement sensors, we estimate the road signs parameters.Results show that the described calculation methodology offers a correct estimation for all types of traffic signs

Road Sign Analysis Using Multisensory Data

This paper deals with the problem of estimating the following road sign parameters: height, dimensions, visibility distance and partial occlusions. This work belongs to a framework whose main applications involve road sign maintenance, driver assistance, and inventory systems. From this paper we suggest a multisensory system composed from two cameras, a GPS receiver, and a distance measurement device,all of them installed in a car. The process consists of several steps which include road sign detection, recognition and tracking , and road signs parameters estimation. From some trigonometric properties, and a camera model, the information provided by the tracking subsystem and the distance measurement sensors, we estimate the road signs parameters.Results show that the described calculation methodology offers a correct estimation for all types of traffic signs

Assistive Robot with an AI-Based Application for the Reinforcement of Activities of Daily Living: Technical Validation with Users Affected by Neurodevelopmental Disorders

In this work, we propose the first study of a technical validation of an assistive robotic platform, which has been designed to assist people with neurodevelopmental disorders. The platform is called LOLA2 and it is equipped with an artificial intelligence-based application to reinforce the learning of daily life activities in people with neurodevelopmental problems. LOLA2 has been integrated with an ROS-based navigation system and a user interface for healthcare professionals and their patients to interact with it. Technically, we have been able to embed all these modules into an NVIDIA Jetson Xavier board, as well as an artificial intelligence agent for online action detection (OAD). This OAD approach provides a detailed report on the degree of performance of a set of daily life activities that are being learned or reinforced by users. All the human–robot interaction process to work with users with neurodevelopmental disorders has been designed by a multidisciplinary team. Among its main features are the ability to control the robot with a joystick, a graphical user interface application that shows video tutorials with the activities to reinforce or learn, and the ability to monitor the progress of the users as they complete tasks. The main objective of the assistive robotic platform LOLA2 is to provide a system that allows therapists to track how well the users understand and perform daily tasks. This paper focuses on the technical validation of the proposed platform and its application. To do so, we have carried out a set of tests with four users with neurodevelopmental problems and special physical conditions under the supervision of the corresponding therapeutic personnel. We present detailed results of all interventions with end users, analyzing the usability, effectiveness, and limitations of the proposed technology. During its initial technical validation with real users, LOLA2 was able to detect the actions of users with disabilities with high precision. It was able to distinguish four assigned daily actions with high accuracy, but some actions were more challenging due to the physical limitations of the users. Generally, the presence of the robot in the therapy sessions received excellent feedback from medical professionals as well as patients. Overall, this study demonstrates that our developed robot is capable of assisting and monitoring people with neurodevelopmental disorders in performing their daily living tasks.This research was funded by project AIRPLANE, with reference PID2019-104323RB-C31, of Spain’s Ministry of Science and Innovation

Assessment and counseling to get the best efficiency and effectiveness of the assistive technology (MATCH): study protocol

Clinical Trials ID: NCT04723784[Abstract] Aims: To determine the psychosocial impact of assistive technology(AT) based on robotics and artificial intelligence in the life of people with disabilities. Background: The best match between any person with disabilities and its AT only can be gotten through a complete assessment and monitoring of his/her needs, abilities, priorities, difficulties and limitations. Without this analysis, it's possible that the device won't meet the individual's expectations. Therefore, it is important that any project focused on the development of innovating AT for people with disabilities includes the perspective of outcome measures as an important phase of the research. In this sense, the integration of the assessment, implementation process and outcome measures is crucial to guarantee the transferability for the project findings and to get the perspective from the final user. Methods: Pilot study, with prospective, longitudinal and analytical cohort. The study lasts from July 2020 until April 2023. The sample is formed by people with disabilities, ages from 2-21, that will participate from the first stage of the process (initial assessment of their abilities and needs) to the final application of outcome measures instruments (with a complete implication during the test of technology). Discussion: Only with the active participation of the person is possible to carry out a user-centered approach. This fact will allow us to define and generate technological solutions that really adjust to the expectations, needs and priorities of the people with disabilities, avoiding the AT from being abandoned, with the consequent health and social spending.Ministerio de Ciencia e Innovación (España); PID2019-104323RB-C31Ministerio de Ciencia e Innovación (España); PID2019-104323RB-C32Ministerio de Ciencia e Innovación (España); PID2019-104323RB-C33Ministerio de Ciencia e Innovación (España); PID2019-104323RB-C3