The chosen solution is based on a client-server architecture and the object recognition is based on local features. The study focuses on the comparison, in terms of time and performance, of the Scale-Invariant Feature Transform (SIFT), the Speeded Up Robust Features (SURF), the Nearest Neighbor Search (NNS) match and a k-means trees based search. It was found that SIFT outperforms SURF in terms...

Behavioral theory in geography attempts to describe and explain the spatial activities of individuals in terms of fundamental perceptual and cognitive processes. As applied to surfing, behavioral theory can give us greater insight into localism (territoriality) and provides a context for understanding the complex cognitive processes involved in choosing where to surf and in choosing where to pa...

In order to extract interest objects in low quality image sequences from fisheries management, this paper proposes a new significant feature extraction method based on cascade framework. This algorithm involves preprocessing image sequences, clipping interesting areas, extracting SURF features, removing boundary features, and acquiring significant features with interesting objects. We apply our...

Achieving highly accurate feature extraction in a short period of time is very important for space applications based on computer vision algorithms, such as with the ExoMars programme of ESA. The paper describes a HW/SW co-design scheme using FPGAs to speed-up the SURF algorithm when executed on a low computational power CPU. It performs algorithmic analysis and restructures the SURF steps lead...

The heat transfer process is an important part of energy utilization and conversion, boiling one the most significant effective modes in use. Enhancing can directly improve use efficiency promote sustainable development industry. Surfaces with mixed wetting topologies have been proven to possess potential enhance transfer. However, promoting mechanism these types surfaces requires further clari...

We present an improved self-localization estimation algorithm in this paper. The algorithm uses a modified SURF method to extract the interest points, using it to extract the orientation and a descriptor of the interest point in order to lessen the computation time. A robot using this method can estimate its indoor self-localization according to matched interest points. A number of intermediate...

The paper describes an image matching method based on visual attention and SURF keypoints. Biologically inspired visual attention system is used to guide local interest point detection. Interest points are represented with SURF descriptors. One–to–one symmetric search is performed on descriptors to select a set of matched interest point pairs. Pairs are then weighted according to attention dist...

In this paper, we propose an ORB hardware accelerator design. Feature-based SIFT and SURF hardware accelerators that detect features in real-time require high hardware costs. To overcome this disadvantage, an ORB algorithm consisting of simple calculations was designed as the hardware accelerator. A comparison between the proposed ORB hardware accelerator with SIFT and SURF accelerators reveale...

An experiment tested whether people orient to and encode pictures selected from a Web site differently, depending on whether the pictures were selected by searching or surfing. Participants in the search condition spent more time selecting pictures than the participants in the surf condition spent. The pictures chosen in the search condition elicited cardiac orienting, while pictures chosen in ...