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The recent light field imaging technology has been attracting a lot of interests due to its potential applications in a large number of areas including Virtual Reality, Augmented Reality (VR/AR), Teleconferencing, and E-learning. Light Field (LF) data is able to provide rich visual information such as scene rendering with changes in depth of field, viewpoint, and focal length. However, Light Field...
This paper proposes a joint source channel-coding scheme based on a multi-encoder and inertial navigation module to solve the problem of poor wireless channel environment and high bit error rate. The encoder consists of three independent channels from the same source encoding the video imager for different H.264 encoding compression ratio. The propsed scheme aims to improve the system robustness under...
Cross-modal hashing is usually regarded as an effective technique for large-scale textual-visual cross retrieval, where data from different modalities are mapped into a shared Hamming space for matching. Most of the traditional textual-visual binary encoding methods only consider holistic image representations and fail to model descriptive sentences. This renders existing methods inappropriate to...
Person re-identification is best known as the problem of associating a single person that is observed from one or more disjoint cameras. The existing literature has mainly addressed such an issue, neglecting the fact that people usually move in groups, like in crowded scenarios. We believe that the additional information carried by neighboring individuals provides a relevant visual context that can...
This work presents images encoding and decoding using the theory of conformal mapping. The conformal mapping theory made changes in the domain of problems without modifying physical characteristics between the domains. Images were utilized and are transported between domains using transformation functions like encrypt keys. Developed method showed to be able to preserve original images characteristics...
The necessity of performing multispectral and hyperspectral image compression on multicore processor devices running on-board satellites has increased as spectral remote sensing devices produce a high amount of data. Multispectral and hyperspectral instruments acquire images that need compressing before being sent to Earth, because the bandwidth used for transmitting images is a limited resource....
This paper describes experimental evaluations of encoding parameters that are appropriate for MPEG-4 Audio Lossless Coding (ALS) to compress high-resolution audio. MPEG-4 ALS Simple Profile defines the values of encoding parameters, such as the maximum sampling frequency and quantization bit depth, for making it easier to implement in the receiving applications. However, ALS Simple Profile does not...
For large-scale visual search, highly compressed yet meaningful representations of images are essential. Structured vector quantizers based on product quantization and its variants are usually employed to achieve such compression while minimizing the loss of accuracy. Yet, unlike binary hashing schemes, these unsupervised methods have not yet benefited from the supervision, end-to-end learning and...
To compress large datasets of high-dimensional descriptors, modern quantization schemes learn multiple codebooks and then represent individual descriptors as combinations of codewords. Once the codebooks are learned, these schemes encode descriptors independently. In contrast to that, we present a new coding scheme that arranges dataset descriptors into a set of arborescence graphs, and then encodes...
Omnidirectional imaging, also known as 360° and spherical imaging, records all 360° of a scene from a specific spatial position, thus offering the user the capability to enjoy three rotational degrees of freedom (3-DoF). To offer a good quality of experience, omnidirectional imaging requires very high bitrates as high spatial resolution are a must and, ideally, also high frame rates. Due to the lack...
Virtual view synthesis is a key component of multi-view imaging systems that enable visual immersion environments for emerging applications, e.g., virtual reality and 360-degree video. Using a small collection of captured reference view-points, this technique reconstructs any view of a remote scene of interest navigated by a user, to enhance the perceived immersion experience. We carry out a convexity...
The paper is focused on use of Pulse Coupled Neural Network (PCNN) in the image steganography based on the research in the field of invariant image recognition. In general, steganography deals with data concealing in the cover mediums which can be freely accessible or transmitted by various communication channels without any restriction. A suitable position of hidden message is crucial for a successful...
In this paper, we proposed a fast coding unit (CU) size decision algorithm for High Efficiency Video Coding (HEVC) medical image lossless coding. In detailed, we used the coding information obtained after checking the first two prediction unit (PU) modes inter 2N×2N and Skip to determine whether or not to continue partitioning the current CU. Eight features are extracted from the coding information...
Sparse Modeling Representative Selection (SMRS) has been recently proposed for finding the most relevant instances in datasets. This method deploys a data self-representativeness coding in order to infer a coding matrix that is regularized with a row sparsity constraint. The method assumes that the score of any sample is set to the L2 norm of the corresponding row in the coding matrix. Since the SMRS...
In free viewpoint television (FTV) application scenario, views that synthesized with depth image-based rendering (DIBR) techniques mainly contain special artifacts like geometric distortions. These artifacts may affect the structure of images/videos by changing the global contour characteristics and thus are annoying for human observers. Context tree based contour coding scheme can be a good tool...
Existing methods for layer-based backward compatible high dynamic range (HDR) image and video coding mostly focus on the rate-distortion optimization of base layer while neglecting the encoding of the residue signal in the enhancement layer. Although some recent studies handle residue coding by designing function based fixed global mapping curves for 8-bit conversion and exploiting standard codecs...
Current light field compression techniques lack robustness to handle both rate-distortion optimized motion compensation as well as latency during the encoding and decoding process. This paper focuses on a contribution approach that uses advanced frame prediction with affine and translational motion models and optimized view prediction structures. This method allows a significant compression performance...
The representation of data in terms of its statistical properties is valuable in many applications. This work uses statistics obtained from 4D scene geometry to characterize, in terms of redundancy, the content produced by lenslet-based light field cameras and by high-density arrays of cameras for the JPEG Pleno Call for Proposals on Light Field Coding. This paper proposes a novel so-called geometric...
Texture classification has been extensively studied in computer vision. Recent research shows that the combination of Fisher vector (FV) encoding and convolutional neural network (CNN) provides significant improvement in texture classification over the previous feature representation methods. However, by truncating the CNN model at the last convolutional layer, the CNN-based FV descriptors would not...
Human action recognition is a challenging and active research area in computer vision. In this paper, we propose a simple yet effective method, called the locality-constrained linear coding (LLC) based two-dimensional spatial-temporal templates, to learn a discriminative representation for human action recognition. Our proposed method calculates twodimensional spatial-temporal templates from each...
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