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Since the born of intelligence tests, there have been a debate about the praticai use of intelligence tests, also with a lots of critics about the nature and the data we can derive from them. Perhaps the study of intelligence tests could be divided in different historical steps, in newer steps intelligence test were used and analyzed according to more detailed psychometrical bases and aiming to define...
The success of sparse representation, in face recognition and visual tracking, has attracted much attention in computer vision in spite of its computational complexity. These sparse representation-based methods assume that the coding residual follows either Gaussian or Laplacian distribution, which may not be accurate enough to describe the coding residuals in real scenarios. In order to deal with...
Software is modularized to make its high complexity manageable. However, a multitude of modularization criteria exists and is applied. Hence, to extend, reuse, or restructure a system, it is important for developers to understand which criteria have been used. To this end, we provide an interactive visualization approach that compares the current modularization of a system to several software clustering...
Three-dimensional (3D) images and video have been around for decades in a variety of formats and supported by different technologies. In the recent past, these technologies have been given increasing attention from both academia and industry mainly due to advances in capture, coding, transmission and display technologies. 3D video has evolved from stereoscopic towards multi-view video plus depth,...
In this recent world, almost everything is getting digitized rapidly. A text based video retrieval system is degrading the performance with respect to user's perception these days. So it's time to move on to the content based retrieval approach to a video. The effective implementation of this system can be done by revision of the content based video retrieval style. Content Based Video Retrieval (CBVR)...
Visual feature descriptors have been successfully deployed in a wide range of applications, e.g. visual retrieval and analysis. To transmit these descriptors over bandwidth-limited networks, a high effciency feature coding technique is highly desired to maximize compression capability and achieve compact feature representations. In this paper, a hybrid visual feature descriptor compression framework...
A video coding system is presented that partitions the scene into "visual structures" anda residual "background" layer. A low-level representation ("track-template") of visual structures is proposed that exploits their temporal redundancy. A dictionary of track-templates is constructed that is used to encode video frames. We make optimal use of the dictionary in terms...
A pixel domain algorithm for low complexity perceptual image coding is proposed. The algorithm exploits a combination of downsampling, predictive coding and just-noticeable difference (JND) model. Downsampling is performed adaptively on the input image based on regions-of-interest (ROI) identified by measuring the downsampling distortions against the visibility thresholds given by the JND model. The...
In this paper, we shall critically appraise sparse representation based denoising applications. An essential task for this framework is dictionary learning. Our novel proposition involves learning such a dictionary not only by analyzing the distribution of training data in the metric space but also exploiting local nature of the visual scene. Subsequently, the learning scheme is further developed...
In this work we present several methods for fast integer motion estimation of videos recorded aboard an Unmanned Aerial Vehicle (UAV). Different from related work, the field depth is not considered to be consistent. The novel methods designed for low complexity MV prediction in H.264/AVC and analysis hereof include histogram-based prediction, constant global motion, and modification of the candidate...
To provide more powerful video enabled applications, e.g. in video surveillance environments, it is increasingly more critical not only to have access to the decoded video but also to, e.g. efficiently search for similar videos. In this context, this paper proposes a feature-based video coding solution adopting a hybrid approach where both pixels and local visual features are exploited for coding...
In image classification and retrieval, the semantic gap is the major challenge. It characterizes the difference between human perception of a concept and how it can be represented using machine level language. Bag of visual words is a well-known efficient method for image representation, however it showed some limitations. The loss of information during the vector quantization process is one of these...
In this paper, a new kind of Fisher Vector (FV) model, named Scale FV (ScaleFV), is proposed to ameliorate visual feature encoding for human action recognition. Although several researches have been proposed for feature encoding, the temporal scale information is almost ignored. Similar to the spatial scale information which has shown to be important in extracting and encoding visual features, the...
In this paper, a new method is proposed to automatically stage the placental maturity from B-mode ultrasound (US) images based on multi-layer Fisher vector (MFV) and densely sampled visual features. The proposed method first densely extracts visual features at a regular grid based on dense sampling instead of a few unreliable interest points. These features are clustered using generative Gaussian...
To remove the information redundancy among blocks, quadtree-based block partitioning is used in High Efficiency Video Coding (HEVC). In this paper, we propose a perceptual block merging method for quadtree-based partitioning in HEVC based on the disorderly concealment effect in human perception. We segment a frame into orderly and disorderly regions using a free-energy based just-noticeable-difference...
Dictionary learning method based on sparse coding has been widely used in visual tracking, since it has good performance in terms of encoding target appearance. Currently, most of the visual tracking algorithms based on dictionary learning update the dictionary with tracking results in tracking process. Consequently, the total error accumulated over time, and even cause the failure of tracking. In...
This paper presents a novel object tracking method based on approximated Locality-constrained Linear Coding (LLC). Rather than using a non-negativity constraint on encoding coefficients to guarantee these elements nonnegative, in this paper, the non-negativity constraint is substituted for a conventional l2 norm regularization term in approximated LLC to obtain the similar nonnegative effect. And...
The bandwidth and storage restrictions of consumer devices and conventional delivery infrastructures on stereoscopic 3D video require efficient compression methods to save the bandwidth and preserve the perceptive quality at the same time. Compression efficiency is actually determined as the visual quality achieved for a certain amount of bitrate. In this paper, a perception aware coding scheme is...
For feature representation of pedestrian recognition, a hybrid hierarchical feature representation method which combines representation ability of bag of words model and depth layered with learning adaptability is presented. This method first uses HOG local descriptor for local features extraction, and then encoding the feature by a depth of layered coding method, the layered coding method by spatial...
In this paper we propose a novel approach to video summarization that is based on the coherency analysis of segmented video frames as represented by region adjacency graphs. Similar segments across consecutive region adjacency graphs are matched and tracked using an efficient graph matching technique. Shot boundaries are detected based on a coherency score that measures the appearances and disappearances...
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