Research on Vocabulary Sizes and Codebook Universality

Liu, Weixue; Hou, Jian; Karimi, Hamid Reza

doi:10.1155/2014/697245

Cited by 3 publications

(3 citation statements)

References 29 publications

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“…Swathi Rao [33] presented a technique in which image feature vectors are calculated using different classes of dense SIFT and they are quantized to visual words. Liu et al [34] analysed the associations among the vocabulary size, classification performance, and universality of codebooks. Subhransu Maji et al [35] presented a technique with nonlinear kernel SVM which show significant progress in image classification.…”

Section: Related Workmentioning

confidence: 99%

Enhancing Scalability of Image Retrieval Using Visual Fusion of Feature Descriptors

Balammal@Geetha¹,

Muthukkumar²,

Seenivasagam³

2022

Intelligent Automation &Amp; Soft Computing

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Content-Based Image Retrieval (CBIR) is an approach of retrieving similar images from a large image database. Recently CBIR poses new challenges in semantic categorization of the images. Different feature extraction technique have been proposed to overcome the semantic breach problems, however these methods suffer from several shortcomings. This paper contributes an image retrieval system to extract the local features based on the fusion of scale-invariant feature transform (SIFT) and KAZE. The strength of local feature descriptor SIFT complements global feature descriptor KAZE. SIFT concentrates on the complete region of an image using high fine points of features and KAZE ponders on details of a boundary. The fusion of local feature descriptor and global feature descriptor boost the retrieval of images having diverse semantic classification and also helps in achieving the better results in large scale retrieval. To enhance the scalability of image retrieval bag of visual words (BoVW) is mainly used. The fusion of local and global feature representations are selected for image retrieval for the reason that SIFT effectively captures shape and texture and robust towards the change in scale and rotation, while KAZE have strong response towards boundary and changes in illumination. Experiments conducted on two image collections, namely, Caltech-256 and Corel 10k demonstrate the proposed scheme appreciably enhanced the performance of the CBIR compared to state-of-the-art image retrieval techniques.

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Section: Related Workmentioning

confidence: 99%

Enhancing Scalability of Image Retrieval Using Visual Fusion of Feature Descriptors

Balammal@Geetha¹,

Muthukkumar²,

Seenivasagam³

2022

Intelligent Automation &Amp; Soft Computing

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“…The interest points detector identifies a set of salient regions from an image. It provides stable and discriminative interest points that are robust to illumination variation [38]. The interest points detector, besides providing a distinctive set of interest points, is also more computationally efficient [39].…”

Section: Stage 1: Interest Points Detectionmentioning

confidence: 99%

Fuzzy encoding with hybrid pooling for visual dictionary in food recognition

Razali

Manshor

Halin

et al. 2021

IJEECS

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<span>Tremendous number of f food images in the social media services can be exploited by using food recognition for healthcare benefits and food industry marketing. The main challenges in food recognition are the large variability of food appearance that often generates a highly diverse and ambiguous descriptions of local feature. Ironically, the ambiguous descriptions of local feature have triggered information loss in visual dictionary constructions from the hard assignment practices. The current method based on hard assignment and Fisher vector approach to construct visual dictionary have unexpectedly cause errors from the uncertainty problem during visual word assignation. This research proposes a method of combination in soft assignment technique by using fuzzy encoding approach and maximum pooling technique to aggregate the features to produce a highly discriminative and robust visual dictionary across various local features and machine learning classifiers. The local features by using MSER detector with SURF descriptor was encoded by using fuzzy encoding approach. Support vector machine (SVM) with linear kernel was employed to evaluate the effect of fuzzy encoding. The results of the experiments have demonstrated a noteworthy classification performance of fuzzy encoding approach compared to the traditional approach based on hard assignment and Fisher vector technique. The effects of uncertainty and plausibility were minimized along with more discriminative and compact visual dictionary representation.</span>

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“…The use of a codebook, a document containing a list of codes, was created based on the Principal Luxury Brand Dimensions model that guided its structure so that it could appropriately capture data relevant to brands' marketing strategies, both traditional and digital (Moreno, Egan, & Brockman, 2011). Codebooks are essential tools in categorizing images and content-based text (Liu, Hou, & Karimi, 2014). The theoretical framework selected for coding was the Principal Luxury Brand Dimensions (Fionda & Moore, 2009); it is defined as the nine principal dimensions that make up a luxury brand.…”

Section: Phase 2: Digital Mediamentioning

confidence: 99%

Luxury fashion advertising: transitioning in the age of digital marketing

Lamoureux¹

2021

Preprint

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Many luxury retailers fear embracing digital touchpoints, believing it could diminish a brand’s integrity. This study explored luxury fashion brands’ transition from traditional marketing strategies into the current “digital age” and experiential economy. The research encompassed a 2-phase qualitative content analysis: Phase 1 used an inductive approach that analyzed and categorized print advertisement images from Vogue US 1980 and 2013 into 3 major categories—types of product or service, overall presentation, and overall appearance of digital content. Phase 2 consisted of a deductive approach that examined Chanel’s and Burberry’s online and social touchpoints. Findings showed that both luxury retailers understand the importance of aligning and maintaining a consistent, appealing brand image across all marketing channels to guarantee success. Marketers and managers must pay attention to the aforementioned constructs if they wish to maintain consumer brand loyalty and emotional engagement by transitioning from traditional into digital marketing strategies.

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Research on Vocabulary Sizes and Codebook Universality

Cited by 3 publications

References 29 publications

Enhancing Scalability of Image Retrieval Using Visual Fusion of Feature Descriptors

Enhancing Scalability of Image Retrieval Using Visual Fusion of Feature Descriptors

Fuzzy encoding with hybrid pooling for visual dictionary in food recognition

Luxury fashion advertising: transitioning in the age of digital marketing

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