Real-time classification of vehicle types within infra-red imagery.

Real-time classification of vehicles into sub-category types poses a significant challenge within infra-red imagery due to the high levels of intra-class variation in thermal vehicle signatures caused by aspects of design, current operating duration and ambient thermal conditions. Despite these challenges, infra-red sensing offers significant generalized target object detection advantages in terms of all-weather operation and invariance to visual camouflage techniques. This work investigates the accuracy of a number of real-time object classification approaches for this task within the wider context of an existing initial object detection and tracking framework. Specifically we evaluate the use of traditional feature-driven bag of visual words and histogram of oriented gradient classification approaches against modern convolutional neural network architectures. Furthermore, we use classical photogrammetry, within the context of current target detection and classification techniques, as a means of approximating 3D target position within the scene based on this vehicle type classification. Based on photogrammetric estimation of target position, we then illustrate the use of regular Kalman filter based tracking operating on actual 3D vehicle trajectories. Results are presented using a conventional thermal-band infra-red (IR) sensor arrangement where targets are tracked over a range of evaluation scenarios

Real-time construction and visualisation of drift-free video mosaics from unconstrained camera motion

This work proposes a novel approach for real-time video mosaicking facilitating drift-free mosaic construction and visualisation, with integrated frame blending and redundancy management, that is shown to be flexible to a range of varying mosaic scenarios. The approach supports unconstrained camera motion with in-sequence loop closing, variation in camera focal distance (zoom) and recovery from video sequence breaks. Real-time performance, over extended duration sequences, is realised via novel aspects of frame management within the mosaic representation and thus avoiding the high data redundancy associated with temporally dense, spatially overlapping video frame inputs. This managed set of image frames is visualised in real time using a dynamic mosaic representation of overlapping textured graphics primitives in place of the traditional globally constructed, and hence frequently reconstructed, mosaic image. Within this formulation, subsequent optimisation occurring during online construction can thus efficiency adjust relative frame positions via simple primitive position transforms. Effective visualisation is similarly facilitated by online inter-frame blending to overcome the illumination and colour variance associated with modern camera hardware. The evaluation illustrates overall robustness in video mosaic construction under a diverse range of conditions including indoor and outdoor environments, varying illumination and presence of in-scene motion on varying computational platforms