This paper propose an effective approach for detecting and tracking moving vehicles in nighttime traffic scenes. Vehicles were detected automatically from video sequences at nighttime by constructing the MILBoost model. At first, we extract SIFT feature using SIFT feature extraction algorithm, which is used to characterize moving vehicles in nighttime. Then MILBoost model is used for the on-roa...

Transmission and storage of local feature descriptors are of critical importance for mobile visual search applications. We perform a comprehensive survey of Scale Invariant Feature Transform (SIFT) compression schemes proposed in the literature and evaluate them in a common framework. Further, we compare the different schemes to the recently proposed low bit-rate Compressed Histogram of Gradien...

In this paper, we describe an approach for the automatic modality classification in medical image retrieval task of the 2010 CLEF cross-language image retrieval campaign (ImageCLEF). This work is focused on the process of feature extraction from medical images and fusion the different extracted visual feature and textual feature for modality classification. To extract visual features from the i...

Video has become an important element of multimedia computing and communication environments, with applications as varied as broadcasting, education, publishing and military intelligence. In Video Retrieval system, each video that is stored in the database has its features extracted and compared to the features of the query image. Proposed work is to retrieve video from the database by giving q...

This paper presents a complete method for vehicle detection and tracking in a fixed setting based on computer vision. Vehicle detection is performed based on Scale Invariant Feature Transform (SIFT) feature matching. With SIFT feature detection and matching, the geometrical relations between the two images is estimated. Then, the previous image is aligned with the current image so that moving v...

UAV remote sensing is characterized by fast speed and flexibility and applied widely. The extraction and matching for feature point of UAV image is a foundational work in the application of UAV remote sensing. SIFT is a currently widely used feature point extraction algorithm that keeps invariant as the scale changes. It is also invariant as image changes in other aspects. Meanwhile it maintain...

Development of various image descriptors has greatly contributed to the advancement in image retrieval. Image descriptors can be made invariant to various image changes. In this paper, a new image descriptor is described and its application in image retrieval is evaluated. The descriptor uses the autoencoder concept to reduce the dimension of the feature vector measuing various properties of a ...

This paper proposes a framework of face recognition based on the multi-scale local structures of the face image. While some basic tools in this framework are inherited from the SIFT algorithm, this work investigates and contributes to all major steps in the feature extraction and image matching. New approaches to keypoint detection, partial descriptor and insignificant keypoint removal are prop...

In online display advertising, state-of-the-art Click Through Rate(CTR) prediction algorithms rely heavily on historical information, and they work poorly on growing number of new ads without any historical information. This is known as the the cold start problem. For image ads, current stateof-the-art systems use handcrafted image features such as multimedia features and SIFT features to captu...

This paper provides a new approach to recognize facial expressions. In this paper, facial expression recognition is based on appearance based features or we can say that low level features. We used two different approaches to categories the expression into seven different classes. These classifications based on Scale Invariant Feature Transform (SIFT) and Local Gabor Binary Filter (LGBP). First...