Kernel bandwidth estimation for moving object detection in non-stabilized cameras

The evolution of the television market is led by 3DTV technology, and this tendency can accelerate during the next years according to expert forecasts. However, 3DTV delivery by broadcast networks is not currently developed enough, and acts as a bottleneck for the complete deployment of the technology. Thus, increasing interest is dedicated to ste-reo 3DTV formats compatible with current HDTV video equipment and infrastructure, as they may greatly encourage 3D acceptance. In this paper, different subsampling schemes for HDTV compatible transmission of both progressive and interlaced stereo 3DTV are studied and compared. The frequency characteristics and preserved frequency content of each scheme are analyzed, and a simple interpolation filter is specially designed. Finally, the advantages and disadvantages of the different schemes and filters are evaluated through quality testing on several progressive and interlaced video sequences

Algorithms for sensor validation and multisensor fusion

Existing techniques for sensor validation and sensor fusion are often based on analytical sensor models. Such models can be arbitrarily complex and consequently Gaussian distributions are often assumed, generally with a detrimental effect on overall system performance. A holistic approach has therefore been adopted in order to develop two novel and complementary approaches to sensor validation and fusion based on empirical data. The first uses the Nadaraya-Watson kernel estimator to provide competitive sensor fusion. The new algorithm is shown to reliably detect and compensate for bias errors, spike errors, hardover faults, drift faults and erratic operation, affecting up to three of the five sensors in the array. The inherent smoothing action of the kernel estimator provides effective noise cancellation and the fused result is more accurate than the single 'best sensor'. A Genetic Algorithm has been used to optimise the Nadaraya-Watson fuser design. The second approach uses analytical redundancy to provide the on-line sensor status output μH∈[0,1], where μH=1 indicates the sensor output is valid and μH=0 when the sensor has failed. This fuzzy measure is derived from change detection parameters based on spectral analysis of the sensor output signal. The validation scheme can reliably detect a wide range of sensor fault conditions. An appropriate context dependent fusion operator can then be used to perform competitive, cooperative or complementary sensor fusion, with a status output from the fuser providing a useful qualitative indication of the status of the sensors used to derive the fused result. The operation of both schemes is illustrated using data obtained from an array of thick film metal oxide pH sensor electrodes. An ideal pH electrode will sense only the activity of hydrogen ions, however the selectivity of the metal oxide device is worse than the conventional glass electrode. The use of sensor fusion can therefore reduce measurement uncertainty by combining readings from multiple pH sensors having complementary responses. The array can be conveniently fabricated by screen printing sensors using different metal oxides onto a single substrate

MKS: a multisensor kernel system

Journal ArticleThe multisensor kernel system (MKS) is presented as a means for multisensor integration and data acquisition. This system has been developed in the context of a robot work station equipped with various types of sensors utilizing three-dimensional laser range finder data and two-dimensional camera data. Specific goals that have been achieved include 1) Developing a suitable low-level representation of raw data and/or features extracted from the raw data of the various sensors; 2) Providing a method for efficient reconfiguration of the sensor system in terms of "logical" sensors which map onto physical sensors and computation; and 3) Providing a basis for high-level object modeling techniques

Multisensor knowledge systems

technical reportWe describe an approach which facilitates and makes explicit the organization of the knowledge necessary to map multisensor system requirements onto an appropriate assembly of algorithms, processors, sensors, and actuators. We have previously introduced the Multisensor Kernel System and Logical Sensor Specifications as a means for high-level specification of multisensor systems. The main goals of such a characterization are: to develop a coherent treatment of multisensor information, to allow system reconfiguration for both fault tolerance and dynamic response to environmental conditions, and to permit the explicit description of control. In this paper we show how Logical Sensors can be incorporated into an object-based approach to the organization of multisensor systems. In particular, we discuss: * a multisensor knowledge base, * a sensor specification scheme, and * a multisensor simulation environment. We give an example application of the system to CAD-based 2-D vision