This paper describes a viewpoint invariant learningbased method for counting people in crowds from a single camera. Our method takes into account feature normalization to deal wit...
Most works based on diversity suggest that there exists only weak correlation between diversity and ensemble accuracy. We show that by combining the diversities with the classifica...
Albert Hung-Ren Ko, Robert Sabourin, Alceu de Souz...
In this work we address the general bin-picking problem where 3D data is available. We apply Harmonic Shape Contexts (HSC) features since these are invariant to translation, scale...
In this paper, we present a new voting-based object labeling method that is robust to background clutter. The conventional simple voting method shows very poor performance under c...
In this paper, we propose a method for human tracking using 3D human body model in a video sequence with a monocular moving camera. Tracking a human with unconstrained movement in...
This work contributes to the robotic bin-picking problem, and more specifically to the problem of localizing piled box-like objects. We employ range imagery, and use box-like Supe...
We present a computationally efficient, on-line graph structure estimation method for model-based scene interpretation. Different scenes have different hierarchical graphical mode...
Recently, boosting is used widely in object detection applications because of its impressive performance in both speed and accuracy. However, learning weak classifiers which is on...