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This study aims to investigate the effect of combination of color accent light and white ambient light on the people's preference for living room considering the activities. 60 observers participated the two parts of the study. A psychophysical evaluation experiment was conducted to examine the effects of various illumination settings on preference for the lighting room depending on 5 specific activities...
3D scene understanding is one of the most important problems in the field of computer vision. Although, in the past decades, considerable attention has been devoted on the 2D scene understanding problem, now with the development of the depth sensors (like Microsoft Kinect), the 3D scene understanding has become a very challenging task. Traditionally, the scene understanding problem was considered...
Developers' daily work produces, transforms, and communicates cross-cutting information across applications, including IDEs, emails, Q&A sites, Twitter, and many others. However, these applications function independently of one another. Even though each application has their own effective information management mechanisms, cross-cutting information across separate applications creates a problem...
We carry out image labeling based on probabilistic integration of local, middle and global information. Local information is effective for capturing color and texture pattern. Middle information is obtained from patches which are larger than local regions and is able to incorporate context information. Global information obtained from an entire image helps to decide the presence of categories in the...
This paper presents an automatic event detection system fusing low and mid level features for soccer videos. We first employ an improved approach for Shot Boundary Detection with color and our mean-gradient feature. Then we classify the shots into two view types. We also perform a template-based replay detection for each shot. Play-break sequences are then generated using a rule-based method. We devise...
To manage a massive growth of sport videos, we require to summarize the content into more compact and dominant representation. The previous research projects proposed soccer summarization by using highlights or scene playing; however, they were unable to do it in a given time period. In this paper, we propose an automatic soccer video summarization that can be done within the time constraint. Our...
Crop segmentation is a frequently concerned problem for computer vision applications in agriculture. Tassel is a typical agronomic trait in the crop breeding process. Tassel trait characterization also requires fine-grained shape extraction. However, previous methods are usually dependent of category, which is hard to transfer to other cultivars with different colors. To address this, the goal of...
The huge volume of videos produced by surveillance cameras has increased the demand for the fast and effective video surveillance indexing and retrieval systems. Although environmental condition such as light reflection, illumination changes, shadow, and occlusion can affect the indexing and retrieval result of any video surveillance system, nevertheless the use of reliable and robust object (blob)...
Eye movements can be an important cue to reveal consumer decision processes. Findings from existing studies suggest that the consumer decision process consists of a few different browsing states such as screening and evaluation. To reveal the characteristics and temporal changes of browsing states in catalog browsing situations, this study proposes a hidden semi-Markov-based gaze model, where the...
Most network traffic analysis applications are designed to discover malicious activity by only relying on high-level flowbased message properties. However, to detect security breaches that are specifically designed to target one network (e.g., Advanced Persistent Threats), deep packet inspection and anomaly detection are indispensible. In this paper, we focus on how we can support experts in discovering...
In this paper, we proposed a segmentation approach that not only segment an interest object but also label different semantic parts of the object, where a discriminative model is presented to describe an object in real world images as multiply, disparate and correlative parts. We propose a multi-stage segmentation approach to make inference on the segments of an object. Then we train it under the...
Pairwise and higher order potentials in the Hierarchical Conditional Random Field (HCRF) model play a vital role in smoothing region boundary and extracting actual object contour in the labeling space. However, pairwise potential evaluated by color information has the tendency to over-smooth small regions which are similar to their neighbors in the color space; and the higher order potential associated...
Car re-identification, searching a specific car object from a large-scale car image database, is investigated in this paper. Previous work mainly focuses on fixed pose and overlooks the special appearance. However, avoiding matching other poses would lead to coarse results of the car retrieval. And some special attributes like individual paintings which are greatly helpful for car retrieval have not...
The paper presents information packaging structures in Romanian utterances with the contrast relation, by decomposing them into hierarchies of embedded communicative units. At any level of the hierarchy, communicative units are structured by two or three functional constituents each of them having text and melodic contour. Communicative unit constituents are functional elements at the information...
Identifying similar narrative sections across longer documents would help identify key events within a corpus, enrich understanding of those events, provide a mechanism for organizing corpora according to their event content, and allow for bottom-up testing of theories of narrative. This paper proposes an automated method for narrative alignment across large textual corpora using techniques from natural...
Person re-identification is the task of associating people across cameras with non-overlapping view field. Two key aspects of Person re-identification are the feature representation and metric learning. The feature representation employed should be both discriminative and invariant, which is also our considering in this paper. To enhance person re-identification performance, we propose to combine...
In this paper, we propose new image features called perceptual colour features. The features are based on twenty basic colours called emotional colours, which are used to describe the relationship between colours and emotions in psychological studies. We analyzed a colour image in L*a*b* and L*C*h colour spaces to link to emotions. Then, the perceptual colour features are derived from the histogram...
This paper presents a hybrid image retrieval system which integrates Neural Network and Genetic Algorithm together. Proposed method reduces the semantic imbalance between the machine description and the human semantics of an image by using low-level feature descriptors- HSV color histograms, color moments, and wavelet transform, which matches human perception. These descriptors when used to train...
The motivation behind this work is to explore and pursue benefits of Cognitive Informative and Artificial Intelligence. Computer based Image Analysis and Machine Vision are based on Image Processing Algorithms. Choosing the best concept to comprehend a meaning in natural language generation is one of the tough tasks. A vision system while navigating in an environment should be able to recognize what...
In this paper we present a novel saliency-based technique for the automatic extraction of relevant subjects in digital images. We use enhanced saliency maps to determine the most relevant parts of the images and an image cropping technique on the map itself to extract one or more relevant subjects. The contribution of the paper is two-fold as we propose a technique to enhance the standard GBVS saliency...
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