摘要：Object recognition, detection and tracking in real time is a necessary task in computer vision. There are huge amount of research work have been done in this area. Yet it needs to be more accuracy in reorganization of object. The most objective of this review is to present an overview of the approaches used and also the challenges involved. In this paper we concentrate on different object detection methods, tracking and recognition methods are discuss. Recognition of objects in video can significant benefits to information retrieval including automatic annotation and queries based and content base on the object characteristics. In this paper we proposed an IMKL (Incremental Multiple Kernel Learning) approach to object recognition that initializes on a generic training database and then tunes itself to the classification task at hand.
其他摘要：Object recognition, detection and tracking in real time is a necessary task in computer vision. There are huge amount of research work have been done in this area. Yet it needs to be more accuracy in reorganization of object. The most objective of this review is to present an overview of the approaches used and also the challenges involved. In this paper we concentrate on different object detection methods, tracking and recognition methods are discuss. Recognition of objects in video can significant benefits to information retrieval including automatic annotation and queries based and content base on the object characteristics. In this paper we proposed an IMKL (Incremental Multiple Kernel Learning) approach to object recognition that initializes on a generic training database and then tunes itself to the classification task at hand.
关键词：Image Processing Using MKL Object Detector;local object detector;Global Object detector
