Piano Crossing - Walking on a Keyboard

Piano Crossing is an interactive art installation which turns a pedestrian crossing marked with white stripes into a piano keyboard so that pedestrians can generate music by walking over it. Matching tones are generated when a pedestrian is over a particular stripe or key. A digital camera is directed at the crossing from above. A special computer vision application was developed that maps the stripes of the pedestrian crossing to piano keys and which detects over which key is the center of gravity of every pedestrian in the image at any given moment. Special black stripes are added to the crossing, which represent also the black piano keys. The application consists of two parts: (1) initialization, where the model of the abstract piano keyboard is mapped to the image of the pedestrian crossing and (2) the detection of pedestrians on the crossing so that musical tones can be generated according to their locations. The art installation Piano crossing was presented to the public for the first time during the 51st Jazz Festival in Ljubljana in July 2010

Foreground-Background Segmentation Based on Codebook and Edge Detector

Background modeling techniques are used for moving object detection in video. Many algorithms exist in the field of object detection with different purposes. In this paper, we propose an improvement of moving object detection based on codebook segmentation. We associate the original codebook algorithm with an edge detection algorithm. Our goal is to prove the efficiency of using an edge detection algorithm with a background modeling algorithm. Throughout our study, we compared the quality of the moving object detection when codebook segmentation algorithm is associated with some standard edge detectors. In each case, we use frame-based metrics for the evaluation of the detection. The different results are presented and analyzed.Comment: to appear in the 10th International Conference on Signal Image Technology & Internet Based Systems, 201

Background Subtraction Based on Color and Depth Using Active Sensors

Depth information has been used in computer vision for a wide variety of tasks. Since active range sensors are currently available at low cost, high-quality depth maps can be used as relevant input for many applications. Background subtraction and video segmentation algorithms can be improved by fusing depth and color inputs, which are complementary and allow one to solve many classic color segmentation issues. In this paper, we describe one fusion method to combine color and depth based on an advanced color-based algorithm. This technique has been evaluated by means of a complete dataset recorded with Microsoft Kinect, which enables comparison with the original method. The proposed method outperforms the others in almost every test, showing more robustness to illumination changes, shadows, reflections and camouflage.This work was supported by the projects of excellence from Junta de Andalucia MULTIVISION (TIC-3873), ITREBA (TIC-5060) and VITVIR (P11-TIC-8120), the national project, ARC-VISION (TEC2010-15396), and the EU Project, TOMSY (FP7-270436)