RGBD Datasets: Past, Present and Future

Since the launch of the Microsoft Kinect, scores of RGBD datasets have been released. These have propelled advances in areas from reconstruction to gesture recognition. In this paper we explore the field, reviewing datasets across eight categories: semantics, object pose estimation, camera tracking, scene reconstruction, object tracking, human actions, faces and identification. By extracting relevant information in each category we help researchers to find appropriate data for their needs, and we consider which datasets have succeeded in driving computer vision forward and why. Finally, we examine the future of RGBD datasets. We identify key areas which are currently underexplored, and suggest that future directions may include synthetic data and dense reconstructions of static and dynamic scenes.Comment: 8 pages excluding references (CVPR style

Bypassing the Natural Visual-Motor Pathway to Execute Complex Movement Related Tasks Using Interval Type-2 Fuzzy Sets

In visual-motor coordination, the human brain processes visual stimuli representative of complex motion-related tasks at the occipital lobe to generate the necessary neuronal signals for the parietal and pre-frontal lobes, which in turn generates movement related plans to excite the motor cortex to execute the actual tasks. The paper introduces a novel approach to provide rehabilitative support to patients suffering from neurological damage in their pre-frontal, parietal and/or motor cortex regions. An attempt to bypass the natural visual-motor pathway is undertaken using interval type-2 fuzzy sets to generate the approximate EEG response of the damaged pre-frontal/parietal/motor cortex from the occipital EEG signals. The approximate EEG response is used to trigger a pre-trained joint coordinate generator to obtain desired joint coordinates of the link end-points of a robot imitating the human subject. The robot arm is here employed as a rehabilitative aid in order to move each link end-points to the desired locations in the reference coordinate system by appropriately activating its links using the well-known inverse kinematics approach. The mean-square positional errors obtained for each link end-points is found within acceptable limits for all experimental subjects including subjects with partial parietal damage, indicating a possible impact of the proposed approach in rehabilitative robotics. Subjective variation in EEG features over different sessions of experimental trials is modelled here using interval type-2 fuzzy sets for its inherent power to handle uncertainty. Experiments undertaken confirm that interval type-2 fuzzy realization outperforms its classical type-1 counterpart and back-propagation neural approaches in all experimental cases, considering link positional error as a metric. The proposed research offers a new opening for the development of possible rehabilitative aids for people with partial impairment in visual-motor coordination

A Survey of Applications and Human Motion Recognition with Microsoft Kinect

Microsoft Kinect, a low-cost motion sensing device, enables users to interact with computers or game consoles naturally through gestures and spoken commands without any other peripheral equipment. As such, it has commanded intense interests in research and development on the Kinect technology. In this paper, we present, a comprehensive survey on Kinect applications, and the latest research and development on motion recognition using data captured by the Kinect sensor. On the applications front, we review the applications of the Kinect technology in a variety of areas, including healthcare, education and performing arts, robotics, sign language recognition, retail services, workplace safety training, as well as 3D reconstructions. On the technology front, we provide an overview of the main features of both versions of the Kinect sensor together with the depth sensing technologies used, and review literatures on human motion recognition techniques used in Kinect applications. We provide a classification of motion recognition techniques to highlight the different approaches used in human motion recognition. Furthermore, we compile a list of publicly available Kinect datasets. These datasets are valuable resources for researchers to investigate better methods for human motion recognition and lower-level computer vision tasks such as segmentation, object detection and human pose estimation

Desarrollo de un robot delta para aplicaciones de manipulación de objetos y visión artificial mediante el sensor kinect.

This section details the development of the construction and the technical characteristics of operation of the actuators, control cards, sensors and special software to be used in the Delta parallel type robot. The Delta platform consists of a fixed platform, a mobile platform and a clamp that together have 5 degrees of freedom which is completely maneuverable if requested. The prototype is based on the commercial robot LLC army Delta, the robot has as a specialty the positioning of objects through the replication of movements of the user's hand. The Delta robot will be controlled by the Xbox Kinect sensor version 1.14, which will operate by imitating movements captured by the sensor using artificial vision, providing control and management in real time waiting for easy handling. The implementation of the Delta robot starts by reverse engineering its design taking as reference the LLC army Delta, for the construction the 3D printing method was designed, designing each piece in the AutoCad 2016 environment. The relevant communication tests will be carried out, and operation to verify the accuracy of the robot, once the objectives are reached, the robot tries to serve as inspiration in applications of different control methods in different robotic applications.En esta sección se detalla el desarrollo la construcción y las características técnicas de operación de los actuadores, tarjetas de control, sensores y software especial a utilizar en el robot tipo paralelo Delta. La plataforma Delta está formada por una plataforma fija, una plataforma móvil y una pinza que en conjunto poseen 5 grados de libertad la cual es completamente maniobrable si así se lo demanda. El prototipo está basado en el Robot comercial LLC army Delta, el robot tiene como especialidad el posicionamiento de objetos mediante la réplica de movimientos de la mano del usuario. El robot Delta estará controlado mediante el sensor Kinect de Xbox versión 1.14, que operará mediante la imitación de movimientos capturados por el sensor usando visión artificial, aportando control y manejo en tiempo real esperando un fácil manejo del mismo. La implementación del robot Delta empieza por ingeniería inversa de su diseño tomando como referencia al LLC army Delta, para la construcción se realizó el método de impresión 3D diseñando cada pieza en el entorno AutoCad 2016. Se realizarán las pertinentes pruebas de comunicación, y operación para comprobar la precisión del robot, una vez alcanzado los objetivos el robot procura servir de inspiración en aplicaciones de diferentes métodos de control en diferentes aplicaciones robóticas

Reconocimiento de posición e inclinación de la mano para control de movimiento de una plataforma delta con kinect

El reconocimiento de posición e inclinación de la mano a la generación de movimiento de la misma. Además, presenta el objetivo del estudio cinemático del robot para el análisis geométrico y el análisis inicial Parámetros de diseño que proporcionan plataforma CAD para una mayor implementación. Por último, entregar una interfaz gráfica de usuario que puede controlar los movimientos del robot desde Una computadora a través de Kinect. En este ámbito se propone manejar la plataforma delta, detectando las coordenadas de pose Y la mano de un operador. Como sistema de imagen, se utiliza el equipo Microsoft Kinect®. los Desarrollo algorítmico para el manejo de los datos proporcionados por la plataforma, es Programa de procesamiento de software, creado inicialmente para el diseño gráfico y Prosperó para proyectos de desarrollo Kinect®. Como medio de manejo con Arduino se formula como Un elemento de hardware abierto. Por otro lado, se entrega una propuesta para diseñar un robot delta de Solid Works. Debería Que el trabajo se centra específicamente en el diseño de la plataforma, el procesamiento de Detección de mano y ningún parámetro como la estrategia de la plataforma de planificación de trayectoria o algún control de la misma.The recognition of position and inclination of the hand to the generation of movement thereof. In addition, it presents the goal of cinematic study of robot for geometric analysis and initial design parameters delivering CAD platform for further implementation. Finally, deliver a graphical user interface which can control the movements of the robot from a computer through Kinect. In this scope it is proposed as handling the delta platform, by detecting the pose coordinates and hand of an operator. As imaging system, the Microsoft Kinect® equipment is used. The algorithmic development for handling the data provided by the platform, is done by the Free Software Processing program, initially created for graphic design and systems that have boomed for development projects Kinect®. As drive means using Arduino is formulated as an element of Open Hardware. On the other hand, a proposal for designing a Solid works delta robot is delivered. It should be noted that work specifically focuses on the design of the platform, image processing for detecting hand and no parameter like path planning platform strategy or some control of it.Magíster en Ingeniería ElectrónicaMaestrí