Multi-object Motion Pattern Classification for Visual Surveillance and Sports Video Retrieval
نویسندگان
چکیده
This paper presents a method to classify scenes based on motion information. While they use object trajectories or optical flow field as motion information in previous work, we use the instantaneous motions of multiple objects in each image. In order to deal with variable number of objects in a scene, we use moment statistics as features. Our approach is based on clustering, a form of unsupervised learning, and needs little human intervention. Furthermore, the probabilistic model based clustering makes it easy to detect scenes with novel patterns.
منابع مشابه
Vs-star: A visual interpretation system for visual surveillance
In recent year, intelligent visual surveillance has become more and more important for enhanced security. In this paper, we will introduce some recent work in image and video understanding. First, we will give an introduction of the related video surveillance system in recent years, in particular, we will describe algorithms and systems developed in our group for the automatic interpretation of...
متن کاملObject Tracking and Indexing in H.264/AVC Bitstream Domains
The use of surveillance video recording is mainly based on the activity of monitoring the areas in which the surveillance cameras are located. Consequently, one of the motivations of observing the footage from surveillance video is to locate and identify regions of interest (e.g. suspected moving objects) in the covered areas. The visual information of objects such as color, shape, texture and ...
متن کاملMotion Pattern-Based Video Classification and Retrieval
Today’s content-based video retrieval technologies are still far from human’s requirements. A fundamental reason is the lack of content representation that is able to bridge the gap between visual features and semantic conception in video. In this paper, we propose a motion pattern descriptor, motion texture that characterizes motion in a generic way. With this representation, we design a seman...
متن کاملA Survey on Human Motion Detection and Surveillance
Over years detecting human beings in a video scene of a surveillance system is one of the most active research topics in computer vision. This interest is driven by wide applications in many areas such as virtual reality, smart surveillance and perceptual interface, human gait characterization person counting in a dense crowd, person identification, gender classification, and fall detection for...
متن کاملVideo Surveillance Classification-based Multiple Instance Object Retrieval: Evaluation and Dataset
In this paper we propose a classification-based automated surveillance system for multiple-instance object retrieval task, and its main purpose, to track of a list of persons in several video sources, using only few training frames. We discuss the perspective of designing appropriate motion detectors, feature extraction and classification techniques that would enable to attain high categorizati...
متن کامل