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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
Mesh-based video coding for low bit-rate communications
In this paper, a new method for low bit-rate content-adaptive mesh-based video coding is proposed. Intra-frame coding of this method employs feature map extraction for node distribution at specific threshold levels to achieve higher density placement of initial nodes for regions that contain high frequency features and conversely sparse placement of initial nodes for smooth regions. Insignificant nodes are largely removed using a subsequent node elimination scheme. The Hilbert scan is then applied before quantization and entropy coding to reduce amount of transmitted information. For moving images, both node position and color parameters of only a subset of nodes may change from frame to frame. It is sufficient to transmit only these changed parameters. The proposed method is well-suited for video coding at very low bit rates, as processing results demonstrate that it provides good subjective and objective image quality at a lower number of required bits
Shape Generation using Spatially Partitioned Point Clouds
We propose a method to generate 3D shapes using point clouds. Given a
point-cloud representation of a 3D shape, our method builds a kd-tree to
spatially partition the points. This orders them consistently across all
shapes, resulting in reasonably good correspondences across all shapes. We then
use PCA analysis to derive a linear shape basis across the spatially
partitioned points, and optimize the point ordering by iteratively minimizing
the PCA reconstruction error. Even with the spatial sorting, the point clouds
are inherently noisy and the resulting distribution over the shape coefficients
can be highly multi-modal. We propose to use the expressive power of neural
networks to learn a distribution over the shape coefficients in a
generative-adversarial framework. Compared to 3D shape generative models
trained on voxel-representations, our point-based method is considerably more
light-weight and scalable, with little loss of quality. It also outperforms
simpler linear factor models such as Probabilistic PCA, both qualitatively and
quantitatively, on a number of categories from the ShapeNet dataset.
Furthermore, our method can easily incorporate other point attributes such as
normal and color information, an additional advantage over voxel-based
representations.Comment: To appear at BMVC 201
Airborne LiDAR for DEM generation: some critical issues
Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for DEM generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of
LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for
DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage
and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the highdensity
characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented
Light field super resolution through controlled micro-shifts of light field sensor
Light field cameras enable new capabilities, such as post-capture refocusing
and aperture control, through capturing directional and spatial distribution of
light rays in space. Micro-lens array based light field camera design is often
preferred due to its light transmission efficiency, cost-effectiveness and
compactness. One drawback of the micro-lens array based light field cameras is
low spatial resolution due to the fact that a single sensor is shared to
capture both spatial and angular information. To address the low spatial
resolution issue, we present a light field imaging approach, where multiple
light fields are captured and fused to improve the spatial resolution. For each
capture, the light field sensor is shifted by a pre-determined fraction of a
micro-lens size using an XY translation stage for optimal performance
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