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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...
Visual attention has been successfully applied in structural prediction tasks such as visual captioning and question answering. Existing visual attention models are generally spatial, i.e., the attention is modeled as spatial probabilities that re-weight the last conv-layer feature map of a CNN encoding an input image. However, we argue that such spatial attention does not necessarily conform to the...
Traffic scene recognition is an important and challenging issue in Intelligent Transportation Systems (ITS). Recently, Convolutional Neural Network (CNN) models have achieved great success in many applications, including scene classification. The remarkable representational learning capability of CNN remains to be further explored for solving real-world problems. Vector of Locally Aggregated Descriptors...
This paper investigates the usability of Halftoning-based Block Truncation Coding (HBTC) feature for image retrieval. It assumes that all images in database are stored in scrambled/encrypted format. Firstly, an image feature descriptor is derived from the scrambled/encrypted image. This image feature is subsequently converted into the binary representation to achieve fast similarity measurement. The...
Dermoscopy image is usually used in early diagnosis of malignant melanoma. The diagnosis accuracy by visual inspection is highly relied on the dermatologist's clinical experience. Due to the inaccuracy, subjectivity, and poor reproducibility of human judgement, an automatic recognition algorithm of dermoscopy image is highly desired. In this work, we present a hybrid classification framework for dermoscopy...
In image forensics, detection of image forgeries involving non-linear manipulations have received a great deal of interest in recent past. Median filtering (MF) is one such non-linear manipulation technique which is quite often used in number of applications such as to hide impulse noises. Unlike other linear filtering operations, non-linear characteristics of median filtering makes it harder to detect...
Given a query image, retrieving images depicting the same object in a large scale database is becoming an urgent and challenging task. Recently, Compact Description for Visual Search (CDVS) is drafted by the ISO/IEC Moving Pictures Experts Group (MPEG) to support image retrieval applications, and it has been published as an international standard. Unfortunately, with regard to applications with hugely...
Wireless Capsule Endoscopy (WCE) allows physicians to examine the entire digestive system without any surgical operation. Although it provides a noninvasive imaging approach to access the gastrointestinal (GI) tract, the biggest drawback of this technology is the large numbers of images need to be diagnosed. In this paper, a global and local saliency coding (GLSAC) method is proposed to detect polyps...
In this paper, we present methods for segmenting noisy two-dimensional forward-scan sonar images and classify and model their background. The segmentation approach differentiates the highlight blobs, cast shadows, and the background of sonar images. There is usually little information within relatively large background regions corresponding to the flat sea bottom and (or) water column, as they are...
Hundreds of millions of images are uploaded to the cloud every day. Innovative applications able to analyze and extract efficiently information from such a big database are needed nowadays more than ever. Visual Search is an application able to retrieve information of a query image comparing it against a large image database. In this paper a Visual Search pipeline implementation is presented able...
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...
This paper presents a new Bag-of-Features model (BoF) to enhance the efficiency of automatic image annotation. Since the traditional BoF ignores the semantic of its vocabularies, it cannot be seen as descriptive representation of images in many image applications. To handle this critical limitation, firstly, we propose the RGB compressive texton. By using compressive sensing theory, the image can...
Recently, the latest advances in compact feature representation and feature learning have provided an efficient framework for several visual analysis tasks, such as object recognition. However, when multiple cameras with overlapping fields-of-view are employed, other visual analysis tasks such as depth estimation can be supported and object recognition accuracy can be improved. In this paper the problem...
When different images are presented to two eyes, they compete for perceptual dominance, such that a region of one image is visible while corresponding region of the other is suppressed. This visual phenomenon is called binocular rivalry. Binocular rivalry may be introduced in stereoscopic images of natural scene, leading to strong visual discomfort and visual fatigue. When binocular differences exceed...
Automated human embryo assessment/grading techniques need to be developed to enhance In Vitro Fertilization (IVF) outcome by selecting embryos with highest implantation potentials. Recently, a number of embryo assessment/grading algorithms have been proposed, however, none of these techniques are fully automatic. In addition, they generally suffer from high computational cost, since they perform extensive...
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...
Towards low latency query transmission via wireless link, methods have been proposed to extract compact visual descriptors on mobile device and then send these descriptors to the server at low bit rates in recent mobile image retrieval systems. The drawback is that such on-device feature extraction demands heavy computational cost and large memory space. An alternate approach is to directly transmit...
A novel visual saliency detection algorithm using ant colony optimization and spatiotemporal information in compressed videos is proposed in this paper. Firstly, a graph is constructed for each frame in the video by dividing it into blocks and taking the block as nodes. We extract spatial and temporal features of each node directly from the compressed bitstreams to form the heuristic matrixes. Each...
Content-based image retrieval (CBIR) of medical images is a crucial task that can contribute to a more reliable diagnosis if applied to big data. Recent advances in feature extraction and classification have enormously improved CBIR results for digital images. However, considering the increasing accessibility of big data in medical imaging, we are still in need of reducing both memory requirements...
The choice for image descriptor in a visual navigation system is not straightforward. Descriptors must be distinctive enough to allow for correct localization while still offering low matching complexity and short descriptor size for real-time applications. MPEG Compact Descriptor for Visual Search is a low complexity image descriptor that offers several levels of compromises between descriptor distinctiveness...
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