The aim of this work was to position a Mobile Robot in an Intelligent Space, and this paper presents a sensorial system for measuring differential phase-shifts in a sinusoidally modulated infrared signal transmitted from the robot. Differential distances were obtained from these phase-shifts, and the position of the robot was estimated by hyperbolic trilateration. Due to the extremely severe trade-off between SNR, angle (coverage) and real-time response, a very accurate design and device selection was required to achieve good precision with wide coverage and acceptable robot speed. An I/Q demodulator was used to measure phases with one-stage synchronous demodulation to DC. A complete set of results from real measurements, both for distance and position estimations, is provided to demonstrate the validity of the system proposed, comparing it with other similar indoor positioning systems.

This paper presents an application for counting people through a single fixed camera. This system performs the count distinction between input and output of people moving through the supervised area. The counter requires two steps: detection and tracking. The detection is based on finding people's heads through preprocessed image correlation with several circular patterns. Tracking is made through the application of a Kalman filter to determine the trajectory of the candidates. Finally, the system updates the counters based on the direction of the trajectories. Different tests using a set of real video sequences taken from different indoor areas give results ranging between 87% and 98% accuracies depending on the volume of flow of people crossing the counting zone. Problematic situations, such as occlusions, people grouped in different ways, scene luminance changes, etc., were used to validate the performance of the system.

This paper presents a novel method for calibrating line-scan cameras using a calibration pattern comprising two parallel planes with lines that can be described using known equations. Using pattern geometry and a line that is captured by a line-scan camera, we calculate the 3-D coordinates of the points corresponding to the straight lines of a pattern that is captured by the line-scan camera. These coordinates are used to obtain the intrinsic and extrinsic parameters of the line scan using a standard calibration procedure that is based on a recursive least squares method. In this paper, the procedure of calibration and the results obtained for a specific line scan will be shown; specifically, the obtained median residual error is 0.28 pixel. Also, the repetitiveness of the calibration process was verified for a sequence of 500 times.