Wyner-Ziv side information generation using a higher order piecewise trajectory temporal interpolation algorithm

Distributed video coding (DVC) reverses the traditional coding paradigm of complex encoders allied with basic decoding, to one where the computational cost is largely incurred by the decoder. This enables low-cost, resource-poor sensors to be used at the transmitter in various applications including multi-sensor surveillance. A key constraint governing DVC performance is the quality of side information (SI), a coarse representation of original video frames which are not available at the decoder. Techniques to generate SI have generally been based on linear temporal interpolation, though these do not always produce satisfactory SI quality especially in sequences exhibiting asymmetric (non-linear) motion. This paper presents a higher-order piecewise trajectory temporal interpolation (HOPTTI) algorithm for SI generation that quantitatively and perceptually affords better SI quality in comparison to existing temporal interpolation-based approaches

Techniques for augmenting the visualisation of dynamic raster surfaces

Despite their aesthetic appeal and condensed nature, dynamic raster surface representations such as a temporal series of a landform and an attribute series of a socio-economic attribute of an area, are often criticised for the lack of an effective information delivery and interactivity.In this work, we readdress some of the earlier raised reasons for these limitations -information-laden quality of surface datasets, lack of spatial and temporal continuity in the original data, and a limited scope for a real-time interactivity. We demonstrate with examples that the use of four techniques namely the re-expression of the surfaces as a framework of morphometric features, spatial generalisation, morphing, graphic lag and brushing can augment the visualisation of dynamic raster surfaces in temporal and attribute series

Flow-directed PCA for monitoring networks

Measurements recorded over monitoring networks often possess spatial and temporal correlation inducing redundancies in the information provided. For river water quality monitoring in particular, flow-connected sites may likely provide similar information. This paper proposes a novel approach to principal components analysis to investigate reducing dimensionality for spatiotemporal flow-connected network data in order to identify common spatiotemporal patterns. The method is illustrated using monthly observations of total oxidized nitrogen for the Trent catchment area in England. Common patterns are revealed that are hidden when the river network structure and temporal correlation are not accounted for. Such patterns provide valuable information for the design of future sampling strategies

Object Detection in Videos with Tubelet Proposal Networks

Object detection in videos has drawn increasing attention recently with the introduction of the large-scale ImageNet VID dataset. Different from object detection in static images, temporal information in videos is vital for object detection. To fully utilize temporal information, state-of-the-art methods are based on spatiotemporal tubelets, which are essentially sequences of associated bounding boxes across time. However, the existing methods have major limitations in generating tubelets in terms of quality and efficiency. Motion-based methods are able to obtain dense tubelets efficiently, but the lengths are generally only several frames, which is not optimal for incorporating long-term temporal information. Appearance-based methods, usually involving generic object tracking, could generate long tubelets, but are usually computationally expensive. In this work, we propose a framework for object detection in videos, which consists of a novel tubelet proposal network to efficiently generate spatiotemporal proposals, and a Long Short-term Memory (LSTM) network that incorporates temporal information from tubelet proposals for achieving high object detection accuracy in videos. Experiments on the large-scale ImageNet VID dataset demonstrate the effectiveness of the proposed framework for object detection in videos.Comment: CVPR 201

Multiple relaxations in temporal planning

CRIKEY is a planner that separates out the scheduling from the classical parts of temporal planning. This can be seen as a relaxation of the temporal information during the classical planning phase. Relaxations in planning are used to guide the search. However, the quality of the relaxation greatly affects the performance of the planner, and in some cases can lead the search into a dead end. This can happen whilst separating out the planning and scheduling problems, leading to the production of an unschedulable plan. CRIKEY can detect these cases and change the relaxation accordingly