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Does there exist a compact set of visual topics in form of keyword clusters capable to represent all images visual content within an acceptable error? In this paper, we answer this question by analyzing distribution laws for keywords from image descriptions and comparing with traditional techniques in NLP, thereby
Recently, the development of 3D model database systems and retrieval components are becoming increasingly important due to a rapidly growing amount of available 3D models. This has made the retrieval for specific 3D models become a vital issue. Unfortunately, traditional keyword searching techniques are not always
Image is a powerful medium for expressing one's ideas and rightly confirms the adage, “One picture is worth a thousand words.” In this work, we explore the application of world knowledge in the form of Wikipedia to achieve this objective-literally. In the first part, we disambiguate and rank
This work aims to build a system to suggest tourist destinations based on visual matching and minimal user input. A user can provide either a photo of the desired scenary or a keyword describing the place of interest, and the system will look into its database for places that share the visual characteristics. To that
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.