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To train a scene classifier with good generalization capability, a large number of human labeled training images are often needed. However, a large number of well-labeled training images may not always be available. To alleviate this problem, the web resources-aided scene classification framework was proposed. The present paper is a new development based on our previously proposed framework [1], with...
Logo identification and classification have received considerable attention from both the machine learning and computer vision communities. Vehicle logo recognition (VLR) is used to recognise accurately the manufacturer of a vehicle by using its iconic logo. A VLR system in addition to license plate recognition aims to increase the confidence of vehicle monitoring systems in private environments such...
Image recognition is one of the fundamental problems in multimedia analysis. Typically in the training database, there will be more than one image for each object, however most existing bag-of-features based approaches treat them independently and completely ignore the feature correspondence relationship among them. As a result, features corresponding to the same physical point may be clustered into...
This paper presents a novel and real-time system for interaction with an application or videogame via hand gestures. Our system includes detecting and tracking bare hand in cluttered background using skin detection and hand posture contour comparison algorithm after face subtraction, recognizing hand gestures via bag-of-features and multiclass support vector machine (SVM) and building a grammar that...
This paper discusses the use of the Scale Invariance Feature Transform (SIFT) features for bare hand gesture recognition. In the training stage, we can not use SIFT keypoints of training images directly with a multi-class Support Vector Machine (SVM) to build a training classifier model, because of the space incompatibility of the SIFT keypoints for every training image that contains the hand gesture...
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