International Journal of Information Acquisition

This paper introduces a face detection, classification and counting system that is robust and works in real-time. It tracks multiple people, which is useful for face counting. The classification problem is defined as differentiating and then classifying the front of a face into Asian or non-Asian categories. The first step, is principal component analysis (PCA) for feature generation and independent component analysis (ICA) for feature extraction. Then, we employ support vector machine (SVM) for the training process and combine different SVM classifiers to create new classifiers, which improves the classification rate. Based on this, we can count the number of Asians and non-Asians. Experiments show that our system achieves a classification rate of 82.5% based on a database containing 750 face images from FERET.

This paper discusses the robust, real-time detection of stationary and moving pedestrians utilizing a single car-mounted monochrome camera. First, the system detects potential pedestrians above the ground plane by combining conventional Inverse Perspective Mapping (IPM)-based obstacle detection with the vertical 1D profile evaluation of the IPM detection result. Usage of the vertical profile increases the robustness of detection in low-contrast images as well as the detection of distant pedestrians significantly. A fast digital image stabilization algorithm is used to compensate for erroneous detections whenever the flat ground plane assumption is an inaccurate model of the road surface. Finally, a low-level pedestrian-oriented segmentation and fast symmetry search on the leg region of pedestrians is also presented. A novel approach termed Pedestrian Detection Strip (PDS) is used to improve the calculation time by a factor of six compared to conventional approaches.

The effective automatic location and tracking of a person's lip has been proven to be very difficult in the field of computer vision. A lip segmentation approach is proposed based on wavelet multi-scale edge detection across a lip map. The developed algorithm exploits the spatial interactions between neighboring pixels through wavelet multi-scale edge detection across the lip map. The algorithm produces better segmentation automatically without the need to determine an optimum threshold for each lip image. It has indicated the developed algorithm with superior performance by comparing with some existing lip segmentation algorithms.

This paper addresses the problem of highly accurate, highly speedy, more reliable and fully automatic camera calibration. Our objective is to construct a reliable and fully automatic system to supply a more robust and highly accurate calibration scheme. A checkerboard pattern is used as calibration pattern. After the corner points on image are detected, an improved Delaunay triangulation based algorithm is used to make correspondences between corner points on image and corner points on checkerboard in 3D space. In order to determine precise position of the actual corner points, a geometrical constraint based global curve fitting algorithm has been developed. The experimental results show that the geometrical constraint based method can improve remarkably the performance of the feature detection and camera calibration.

In this paper we use the design of an innovative on-board vision system for a small commercial minirobot to demonstrate the application of the demand compliant design (DeCoDe) method. Vision systems are amongst the most complex sensor systems both in nature and in engineering and thus provide an excellent arena for testing design methods. A review of current design methods for mechatronic systems shows that there are no methods that support or require a complete description of the product system. The DeCoDe method is a step towards overcoming this deficiency. The minirobot robot design is carried from the generic vision system level down to first refinement for a minirobot vision system for visual navigation.

In this paper, the radiation characteristics with respect to the suitability of using homogeneous phantom for testing the compliance of radiation frequency devices are assessed. The Finite-Difference Time-Domain (FDTD) method is applied to analyze the variations of a 900 MHz half-wavelength dipole antenna's biological effects and link performance depending on distance between antenna and human body model. The distance between the surface of the model and the outside exposure source is changed from 25 mm to 1 mm within the range of λ/2π. The distributions of the specific absorption rates (SARs) and the electric fields for various vertical slices of a simplified homogeneous phantom and three anatomical human body trunk models are calculated, respectively. The legs and head have little influence on the radiation characteristics of body-worn, ingestible or implantable wireless devices. The results demonstrate that a homogenous representation of human body is suited for assessing the averaged SARs in human body and confirm that the local energy absorption details and communication link performance need to be analyzed by using the anatomical models or by combining with the worst-case consideration.

We developed a novel catheter operating system with an integrated force sensor for medical applications which included a highly precise master-slave remote control system. This paper explains the system design and control system in detail. As part of our research, we designed a micro force sensor and included it in the system to ensure safe operation in intravascular neurosurgery applications. We performed operation simulation experiments and analyzed the operating errors. The experimental results indicated that the proposed force sensor-based catheter operating system works well and can be controlled remotely, and the force feedback can effectively improve operability at an aneurysm.