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Action recognition has been one of the most popular fields of computer vision. This paper presents a novel approach to action recognition problem using the dimension reduction method, local fisher discriminant analysis, to reduce the dimension of feature descriptors as the preprocessing step after feature extraction. We propose to use sparse matrix and randomized kd-tree to modify and accelerate the...
We present ImmunoExplorer, a web-based multivariate visualization environment that supports exploratory analysis of experimental datasets typical in immunotherapy research. Research advances in immuno-oncology have opened up new frontiers for experimental and clinical research that aims to understand the complex interactions between cancer and the immune systems. Immunotherapy focuses on the development...
Ego-network is built with a specific individual, i.e., the ego, and individuals connected to it, i.e., alter. As an abstraction of connection between individual and outside world, it usually has multiple attributions and has been applied to many research fields. Multivariate ego-network evolution assists users analyzing individual characteristic and hidden pattern in the network. However, most of...
Most augmented reality applications connect virtual information to anchors, i.e. physical places or objects, by using spatial overlays or proximity. However, for industrial use cases this is not always feasible because specific parts must remain fully visible in order to meet work or security requirements. In these situations virtual information must be displayed at alternative positions while connections...
In this paper, we present a novel perceptually-based optimization for the improvement of stereoscopic video coding efficiency. The main idea of this proposed scheme is to adaptively adjust the quantization parameter by taking into account the Human Visual System perceptual characteristics. For this, a saliency map is generated from both views and then segmented into salient and non-salient regions...
Text detection is typically the first step for any text processing such as hand-written text recognition, layout analysis, line detection, or writer identification. This paper describes a new method to detect text in images, particularly in historical document images. For a robust detection, we propose the use of the vesselness filter as a new preprocessing step for text detection. We show, that this...
Visual question answering (VQA) comes as a result of great development in computer vision and natural language processing, which requires deep understanding of images and questions and effective integration of them. Current works on VQA simply concatenated visual and textual features or compared them via dot product, which were unable to eliminate the semantic difference between them. We argue to...
In this paper we introduce a novel method for general semantic segmentation that can benefit from general semantics of Convolutional Neural Network (CNN). Our segmentation proposes visually and semantically coherent image segments. We use binary encoding of CNN features to overcome the difficulty of the clustering on the high-dimensional CNN feature space. These binary codes are very robust against...
Action recognition has been one of the challenging problems in the computer vision community. Most of the recent research work in this area exploits the motion features captured by dense trajectory descriptors. On the other hand, static image classification has seen the rise of deep learning architectures, with evidence that the output of intermediate layers could be successfully employed as a low...
Intra-frame prediction in the High Efficiency Video Coding (HEVC) standard can be empirically improved by applying sets of recursive two-dimensional filters to the predicted values. However, this approach does not allow (or complicates significantly) the parallel computation of pixel predictions. In this work we analyze why the recursive filters are effective, and use the results to derive sets of...
Cultivar identification is an important aspect in agriculture and also a typical task of fine-grained visual categorization (FGVC). In comparison with other common topics in FGVC, studies on this problem are somewhat lagged and limited. In this paper, targeting four Chinese maize cultivars of Jundan No.20, Wuyue No.3, Nongda No.108, and Zhengdan No.958, we first consider the problem of identifying...
We present a novel video representation for human action recognition by considering temporal sequences of visual words. Based on state-of-the-art dense trajectories, we introduce temporal bundles of dominant, that is most frequent, visual words. These are employed to construct a complementary action representation of ordered dominant visual word sequences, that additionally incorporates fine grained...
In contrast to still image analysis, motion information offers a powerful means to analyze video. In particular, motion trajectories determined from keypoints have become very popular in recent years for a variety of video analysis tasks, including search, retrieval and classification. Additionally, cloud-based analysis of media content has been gaining momentum, so efficient communication of salient...
The new quad-tree structure was adopt by High Efficiency Video Coding (HEVC) to partition the Coding Unit (CU). It improved compression efficiency while increased the computational complexity. This paper analysis the percentage of CU depth, the coding time of CU depth and the relationship between the CU depth and the visual saliency. A complexity control algorithm for HEVC with the visual saliency...
Steady-State Visual Evoked Potential (SSVEP) based Brain-Computer Interface (BCI) system is an important BCI modality. It has advantages such as ease of use, little training and high Information Transfer Rate (ITR). Traditional SSVEP based BCI systems are based on the Frequency Division Multiple Access (FDMA) approach in telecommunications. Recently, Time Division Multiple Access (TDMA) was also introduced...
Using EEG source reconstruction with Multiple Sparse Priors (MSP), we investigated the regional brain activity that determines successful memory encoding in two participant groups of high and low accuracy rates. Eighteen healthy young adults performed a sequential fashion of visual Sternberg memory task. The 32-channel EEG was continuously measured during participants performed two 70 trials of memory...
Brain-computer interfacing (BCI) based on steady-state visual evoked potentials (SSVEPs) is one of the most practical BCIs because of its high recognition accuracies and little training of a user. Mixed frequency and phase coding which can implement a number of commands and achieve a high information transfer rate (ITR) has recently been gaining much attention. In order to implement mixed-coded SSVEP-BCI...
Managers are increasingly using online contributions to make hiring decisions. However, it is nontrivial to find the relevant information of candidates in large online, global communities. We present Visual Resume, a novel tool that aggregates information on contributions across two different types of peer production sites (a code hosting site and a technical Q&A forum). Visual Resume displays...
In this paper, we propose a new local descriptor for action recognition in depth images. Our proposed descriptor jointly encodes the shape and motion cues using surface normals in 4D space of depth, time, spatial coordinates and higher-order partial derivatives of depth values along spatial coordinates. In a traditional Bag-of-words (BoW) approach, local descriptors extracted from a depth sequence...
This paper presents a lightweight video sensor node for moving object surveillance using region-of-interest (ROI) based coding and an on-line multi-parameter rate controller. The proposed ROI-based coding scheme determines ROI blocks, pre-processes non-ROI blocks using bit-truncation, and encodes all blocks using Motion JPEG. The on-line rate controller modulates the parameters of the ROI-based coding...
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