Image Summaries using Database Saliency

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Recent years have seen remarkable advancements in saliency estimation methods, mainly due to deep learning models leveraging the widespread availability of real-world images. However, saliency is profoundly shaped by the intricacies of the human visual att ...

Transportation, which deals with moving people and goods around, has a clear impact on the economic development of our society and our well-being. Traditionally, transportation was studied and analyzed using expensive sensors, such as induction loops, that ...

In this work, we resolve a big challenge that most current image quality metrics (IQMs) are unavailable across different image contents, especially simultaneously coping with natural scene (NS) images or screen content (SC) images. By comparison with exist ...

With ever greater computational resources and more accessible software, deep neural networks have become ubiquitous across industry and academia. Their remarkable ability to generalize to new samples defies the conventional view, which holds that complex, ...

A versatile method to automatically classify ice particle habit from various airborne optical array probes is presented. The classification is achieved using a multinomial logistic regression model. For each airborne probe, the model determines the particl ...

We propose a weakly supervised semantic segmentation algorithm that uses image tags for supervision. We apply the tags in queries to collect three sets of web images, which encode the clean foregrounds, the common back- grounds, and realistic scenes of the ...

Pixel-level annotations are expensive and time consuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recently, CNN-based methods have proposed to fine-tune pre-trained networks using im ...

Background: Automated classification using machine learning often relies on features derived from segmenting individual objects, which can be difficult to automate. WND-CHARM is a previously developed classification algorithm in which features are computed ...

When we look at our environment, we primarily pay attention to visually distinctive objects. We refer to these objects as visually important or salient. Our visual system dedicates most of its processing resources to analyzing these salient objects. An ana ...

Fast and accurate salient-object detectors are important for various image processing and computer vision applications, such as adaptive compression and object segmentation. It is also desirable to have a detector that is aware of the position and the size ...

Visual scene recognition deals with the problem of automatically recognizing the high-level semantic concept describing a given image as a whole, such as the environment in which the scene is occurring (e.g. a mountain), or the event that is taking place ( ...

This work extends previous studies on using EEG decoding for automatic image retrieval. We propose an iterative way to integrate the information obtained from the EEG decoding and image processing methods. In the light of real-world BCI applications, we de ...

Many images uploaded to social networks are related to travel, since people consider traveling to be an important event in their life. However, a signiﬁcant amount of travel images on the Internet lack proper geographical annotations or tags. In many cases ...

Finding relations between image semantics and image characteristics is a problem of long standing in computer vision and related fields. Despite persistent efforts and significant advances in the field, today’s computers are still strikingly unable to achi ...

The ability to automatically find objects of interest in images is useful in the areas of compression, indexing and retrieval, re-targeting, and so on. There are two classes of such algorithms – those that find any object of interest with no prior knowledg ...

The perception that we have about the world is influenced by elements of diverse nature. Indeed humans tend to integrate information coming from different sensory modalities to better understand their environment. Following this observation, scientists hav ...

Detection of visually salient image regions is useful for applications like object segmentation, adaptive compression, and object recognition. In this paper, we introduce a method for salient region detection that outputs full resolution saliency maps with ...

Detection of salient image regions is useful for applications like image segmentation, adaptive compression, and region-based image retrieval. In this paper we present a novel method to determine salient regions in images using low-level features of lumina ...

The approach to indexing an image collection depends on the type of data to organize. Satellite images are likely to be searched with latitude and longitude coordinates, medical images are often searched with an image example that serves as a visual query, ...

The ever increasing number of digital images in both public and private collections urges on the need for generic image content analysis systems. These systems need to be capable to capture the content of images from both scenes and objects, in a compact w ...

Image Summaries using Database Saliency

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