Object tracking can be defined as the process of detecting an object of interest from a video scene and keeping track of its motion, orientation, occlusion etc. in order to extract useful information. It is indeed a challenging problem and it’s an important task. Many researchers are getting attracted in the field of computer vision, specifically the field of object tracking in video surveillan...

This article proposes a novel background subtraction (BGS) technique to detect local changes corresponding to the movement of the objects in video scenes. Here we propose an efficient combination of six local features; three existing and three newly proposed. For background modeling and subtraction here a statistical parametric biunique model is proposed. In the proposed BGS scheme, during the ...

Background subtraction (BS) is one of the most commonly encountered tasks in video analysis and tracking systems. It distinguishes the foreground (moving objects) from the video sequences captured by static imaging sensors. Background subtraction in remote scene infrared (IR) video is important and common to lots of fields. This paper provides a Remote Scene IR Dataset captured by our designed ...

a r t i c l e i n f o Keywords: Background subtraction Rough set 3D histon 3D fuzzy histon 3D HRI 3D FHRI Detection of moving objects in the presence of challenging background situations like swaying vegetation, rippling water, camera jitter etc., is known to be a difficult task. Background subtraction is considered to be better than the other approaches in terms of robustness. Its success prim...

A system for tracking humans and detecting human-object interactions in indoor environments is described. A combination of correlogram and histogram information is used to model object and human color distributions. Humans and objects are detected using a background subtraction algorithm. The models are built on the fly and used to track them on a frame by frame basis. The system is able to det...

[1] We have successfully characterized the Clementine HIRES multispectral sensor entirely from inflight measurements. Relative calibration is obtained through dark subtraction (additive) and sensor spatial nonuniformity (multiplicative) on a pixel-by-pixel basis. Relative residuals from frame-to-frame are typically less than 1%. Absolute coefficients are obtained through comparisons with calibr...

This paper proposes a method of noise reduction by pairedmicrophones as a front-end processor for speech recognition systems. This method estimates noises using a subtractive microphone array and subtracts them from the noisy speech signal using the Spectral Subtraction (SS). Since this method can estimate noises analytically and frame by frame, it is easy to estimate noises not depending on th...

Moving object extraction is a critical stage in a measurable 2D and 3D photogrammetric surveillance systems. In order to keep the frame rate of the live video, the chosen automatic method should be fast enough. Moreover, it is important to extract the moving objects precisely to be able to increase the accuracy of the measurements. Prior to the boundary extraction stage, the moving objects must...

Automatic detection of human fall events is a challenging but important function of the real-time surveillance system. The goal of the proposed system is to develop a frame-by-frame fall detection system based on real-time RGB-D camera devices. The proposed system is composed of a complex off-line learning stage which combines several novel machine learning techniques and a series of on-line de...

In this paper, we propose a panorama-based object tracking scheme for wide-view surveillance systems that can detect and track moving objects with a pan-tilt camera. A dynamic mosaic of the background is progressively integrated in a single image using the camera motion informatin. For the camera motion estimation, we calculate affine motion parameters for each frame sequentially with respect t...