Image based Touristic Monument Classification using Graph based Visual Saliency and Scale-Invariant Feature Transform

Kalliatakis, Grigorios; Kounalakis, Tsampikos; Papadourakis, Georgios; Triantafyllidis, Georgios

doi:10.2316/p.2012.779-027

Cited by 2 publications

(3 citation statements)

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“…To achieve this method we have to implement object recognition and classification techniques based on [14,24,25]. First of we have to find the location of an object into an image cluttered mostly by unwanted regions.…”

Section: A Multimodal Processesmentioning

confidence: 99%

Multimodal desktop interaction: The face - object - gesture - voice example

Vidakis

Vlasopoulos

Kounalakis

et al. 2013

2013 18th International Conference on Digital Signal Processing (DSP)

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This paper presents a natural user interface system based on multimodal human computer interaction, which operates as an intermediate module between the user and the operating system. The aim of this work is to demonstrate a multimodal system which gives users the ability to interact with desktop applications using face, objects, voice and gestures. These human behaviors constitute the input qualifiers to the system. Microsoft Kinect multi-sensor was utilized as input device in order to succeed the natural user interaction, mainly due to the multimodal capabilities offered by this device. We demonstrate scenarios which contain all the functions and capabilities of our system from the perspective of natural user interaction.

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Section: A Multimodal Processesmentioning

confidence: 99%

Multimodal desktop interaction: The face - object - gesture - voice example

Vidakis

Vlasopoulos

Kounalakis

et al. 2013

2013 18th International Conference on Digital Signal Processing (DSP)

Self Cite

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“…Li et al analyzed the visual saliency in frequency domain and employed hypercomplex Fourier transform algorithm [27]. In recent years, some new computational models based on visual saliency were proposed in the welding industry, agriculture, food inspection, and so on [28][29][30][31][32]; however, it is fruitless by graph-based visual saliency (GBVS) [33] when the object is a gray-level image, as in Figure 2. Feature extraction refers to the extraction of cartridge crack defect characteristics.…”

Section: An Improved Visual Attention Based Algorithmmentioning

confidence: 99%

“…Then, it was implemented through the calculation of the difference between the fine and coarse scales. Meanwhile, we used the Gabor and Roberts operators [33] separately to generate a direction feature pyramid and an edge feature pyramid for the image. The image pyramid is a simple but efficient tool used to interpret image through a multiresolution method.…”

Section: An Improved Visual Attention Based Algorithmmentioning

confidence: 99%

A Multitarget Visual Attention Based Algorithm on Crack Detection of Industrial Explosives

Shi

Zhang

2018

Mathematical Problems in Engineering

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This paper is a novel study on crack detection of industrial explosives. The proposed algorithm consists of the following steps:(1) image preprocessing was performed according to the defect features of industrial explosives cartridge, and we developed an improved visual attention based algorithm. This proposed algorithm features a parametric analysis that can be implemented on the image according to the conspicuous maps with the introduction of the concept of defect discrimination ; (2) as compared with other algorithms, our method can realize real-time multitarget detection function; (3) a new analysis method, the IPV-WEN algorithm, was proposed to analyze the cartridge defects based on performance indices. Through comparison and experimentation, it was revealed that this method can achieve a detection accuracy of 97.9%, with detection time of 34.51 ms, which satisfied the requirement in the industrial explosives production.

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Image based Touristic Monument Classification using Graph based Visual Saliency and Scale-Invariant Feature Transform

Cited by 2 publications

References 1 publication

Multimodal desktop interaction: The face - object - gesture - voice example

Multimodal desktop interaction: The face - object - gesture - voice example

A Multitarget Visual Attention Based Algorithm on Crack Detection of Industrial Explosives

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