Video activity extraction and reporting with incremental unsupervised learning

The present work presents a new method for activity extraction and reporting from video based on the aggregation of fuzzy relations. Trajectory clustering is first employed mainly to discover the points of entry and exit of mobiles appearing in the scene. In a second step, proximity relations between resulting clusters of detected mobiles and contextual elements from the scene are modeled employing fuzzy relations. These can then be aggregated employing typical soft-computing algebra. A clustering algorithm based on the transitive closure calculation of the fuzzy relations allows building the structure of the scene and characterises the ongoing different activities of the scene. Discovered activity zones can be reported as activity maps with different granularities thanks to the analysis of the transitive closure matrix. Taking advantage of the soft relation properties, activity zones and related activities can be labeled in a more human-like language. We present results obtained on real videos corresponding to apron monitoring in the Toulouse airport in France.

Modeling camera orientation and 3D structure from a sequence of images taken by a perambulating commercial video camera

In this paper we report the degree of reliability of image sequences taken by off-the-shelf TV cameras for modeling camera rotation and reconstructing 3D structure using computer vision techniques. This is done in spite of the fact that computer vision systems usually use imaging devices that are specifically designed for the human vision. Our scenario consists of a static scene and a mobile camera moving through the scene. The scene is any long axial building dominated by features along the three principal orientations and with at least one wall containing prominent repetitive planar features such as doors, windows bricks etc. The camera is an ordinary commercial camcorder moving along the axial axis of the scene and is allowed to rotate freely within the range +/- 10 degrees in all directions. This makes it possible that the camera be held by a walking unprofessional cameraman with normal gait, or to be mounted on a mobile robot. The system has been tested successfully on sequence of images of a variety of structured, but fairly cluttered scenes taken by different walking cameramen. The potential application areas of the system include medicine, robotics and photogrammetry.

Deterministic IIR video deghoster for all ghost carrier phases

It is known that certain video deghoster systems cannot fully process the induced signal derived from the quadrature carrier forming nature of the VSB filter under a multipath condition. A new deterministic IIR deghoster filter structure is given which is capable of deghosting terrestrial video for any relative ghost carrier phase.

Cancellation of residual ghost VSB components from video IIR deghoster systems

Certain deghosters suffer from the presence of distortion caused by the quadrature forming nature of the IF VSB filter operating on a ghosted IF signal. By analysing this a priori effect, a specific deghoster solution is found by using the phase quadrature detected IF signal to cancel the VSB induced ghost quadrature distortions from the detected inphase signal before deghosting takes place.

The concept of a new video detector for ghosted IF signals

The effect of terrestrial television multipath signals on the intermediate frequency (IF) vestigial sideband filter and the video detector are discussed. A new detector is proposed which, by processing the detected phase quadrature information, derives the correct phase for synchronous detection in the presence of multipath effects. This minimizes dispersion and produces a detected video signal with the linear addition of any ghosts.

Object detecting artificial retina

This paper describes the novel use of agent and cellular neural Hopfield network techniques in the design of a self-contained, object detecting retina. The agents, which are used to detect features within an image, are trained using the Hebbian method which has been modified for the cellular architecture. The success of each agent is communicated with adjacent agents in order to verify the detection of an object. Initial work used the method to process bipolar images. This has now been extended to handle grey scale images. Simulations have demonstrated the success of the method and further work is planned in which the device is to be implemented in hardware.

Vidibus: a low-cost, modular bus system for real-time video processing

The advantages of standard bus systems have been appreciated for many years. The ability to connect only those modules required to perform a given task has both technical and commercial advantages over a system with a fixed architecture which cannot be easily expanded or updated. Although such bus standards have proliferated in the microprocessor field, a general purpose low-cost standard for digital video processing has yet to gain acceptance. The paper describes the likely requirements of such a system, and discusses three currently available commercial systems. A new bus specification known as Vidibus, developed to fulfil these requirements, is presented. Results from applications already implemented using this real-time bus system are also given.

Learning enhanced 3D models for vehicle tracking

This paper presents an enhanced hypothesis verification strategy for 3D object recognition. A new learning methodology is presented which integrates the traditional dichotomic object-centred and appearance-based representations in computer vision giving improved hypothesis verification under iconic matching. The "appearance" of a 3D object is learnt using an eigenspace representation obtained as it is tracked through a scene. The feature representation implicitly models the background and the objects observed enabling the segmentation of the objects from the background. The method is shown to enhance model-based tracking, particularly in the presence of clutter and occlusion, and to provide a basis for identification. The unified approach is discussed in the context of the traffic surveillance domain. The approach is demonstrated on real-world image sequences and compared to previous (edge-based) iconic evaluation techniques.