Color Interactive Contents System using Kinect Camera Calibration

Recently, media content that interacts in real time is increasing. In this paper, we introduce a real-time color extraction content system that utilizes the Kinect camera used in ‘COLOR’ media art. The Kinect camera used in the work detects and tracks the joints of the visitors that enter the exhibition space. Kinect detected data is mapped to color calibration in a Unity environment to generate a point cloud video. Get the pixel color of the spine shoulder joint coordinates of the visitor in the point cloud image. The color data is output on the screen in the form of color one, and passes through along with the spectators. Color circle decreases as the distance between the visitors and Kinect increases and the distance increases. When visitors come in and the color circles overlap, color of the mixed part will have an intermediate value between the two color circles. This work shows the form of a person's social movement through the colors that each person has and the mixture of the colors. The technology used in this work differs from other media arts in that it extracted the calibrated image colors separately and advanced the interactive media arts. We will improve the accuracy of the point cloud that corrects the color image and the depth image, and improve the color extraction accuracy of the visitors.

2D In Situ Method for Measuring Plant Leaf Area with Camera Correction and Background Color Calibration

In order to measure the plant leaf area conveniently and quickly in an indoor laboratory and outdoor field, a set of scaffold leaf area measurement systems was designed and manufactured. A 2D in situ method for measuring plant leaf area with camera correction and background color calibration was proposed. The method integrates three subalgorithms: fast calibration and distortion correction algorithm, background color calibration algorithm, and edge error correction algorithm. At the same time, the Visual Studio 2015 and OpenCV 3.4.0 were used to develop and test the algorithm. In order to verify the measurement speed and environmental adaptability of the system, the test was carried out in the complex light disturbance outdoors, and the results were consistent with those in the room. In order to verify the measurement accuracy of the system, this method was used to measure the standard rectangular gauge block of known area and the real leaf area, respectively, and its data were compared with the data measured by Wanshen LA-S plant image analyzer. The results show that both methods have a good stability, and the algorithm proposed in this paper performs better in measurement accuracy and environmental adaptability.

Project-Based Learning Environment: Integration of an Educational Robot Arm with Computer Vision and ROS

Robotics is a science, which aims at controlling mechanical systems through electrical systems and computer techniques. Robotics has a high rate of applicability but, in order to make it easier to comprehend when it comes to learning processes, methodologies that enhance the student's performance and learning curve, like the project-based learning method, are indispensable. The project-based learning technique diverges from the conventional approach, as it makes the many students the object itself of their learning development, by giving them the power of choice and major control over the entire process. This article aims at presenting the project developed by students from the “Robotics and Its Elements” class ministered at Universidade Federal de Ouro Preto - UFOP. The project dealt with concepts, approaches, explanations, and techniques that created a robot-cell (Melfa RV-2AJ and its peripherals) which used the ROS framework system alongside computer vision resources. The robot, after its completion, was able to perform repetitive tasks such as the detection and gathering of specific physical elements – it can manipulate them properly. To make those tasks possible, a Kinect camera was used to obtain data such as the depth and location of the elements which were in the robot's range of grasp. In addition, a detection mechanism derived from the combination of an open source graphic library called OpenCV with the usage of the HSV color system was an important accessory, so that color calibration and orientation addressed properly. Finally, the designated framework (ROS) suited to establish a connection between the robot and its whole operational environment, in order to make the data-sharing and input signal both able to work over the robot's mobility.