This paper presents a survey and a comparative evaluation of recent techniques for moving
cast shadow detection. We identify shadow removal as a critical step for improving object …

With the maturity of sensing and pervasive computing techniques, extensive research is
being carried out in using different sensing techniques for understanding human behaviour …

The integration of data and scientific computation is driving a paradigm shift across the
engineering, natural, and physical sciences. Indeed, there exists an unprecedented …

This paper proposes an end-to-end trainable network, SegFlow, for simultaneously
predicting pixel-wise object segmentation and optical flow in videos. The proposed SegFlow …

Unsupervised video object segmentation (UVOS) aims at segmenting the primary objects in
videos without any human intervention. Due to the lack of prior knowledge about the primary …

Visual object tracking aims to localize the target object of each frame based on its initial
appearance in the first frame. Depending on the input modility tracking tasks can be divided …

Mixture of Gaussians is a widely used approach for background modeling to detect moving
objects from static cameras. Numerous improvements of the original method developed by …

We present a novel framework for learning patterns of motion and sizes of objects in static
camera surveillance. The proposed method provides a new higher-level layer to the …

Research into the methods and techniques used in simulating crowds has developed
extensively within the last few years, particularly in the areas of video games and film …

Tracking-based approaches for abandoned object detection often become unreliable in
complex surveillance videos due to occlusions, lighting changes, and other factors. We …