Voting behavior in one-shot and iterative multiple referenda

The Break-Up of Municipalities – Voting Behavior in Local Referenda

This paper examines the economic and political conditions that influence people’s attitudes regarding a municipality break-up. The theoretical model predicts intra-municipal differences in tax bases, political preferences, and population size to affect the expected gain from secession. The predictions of the model are tested using data on local referenda about municipality partitioning in Swede...

Manipulation of Hamming-based Approval Voting for Multiple Referenda and Committee Elections

Several methods exist for electing committees of representatives and conducting multiple referenda based on approval voting. Recently, a family of rules for approval-based voting using ordered weighted averaging was proposed in [1], ranging from a simple candidate-wise majority (minisum) to egalitarian rule (minimax). Even though the first rule is strategyproof and the second is not, due to its...

One-Shot Video Object Segmentation with Iterative Online Fine-Tuning

Semi-supervised or one-shot video object segmentation has attracted much attention in the video analysis community recently. The OSVOS model [1] achieves state of the art results on the DAVIS 2016 dataset by first fine-turning a CNN model on the first pre-segmented frame of a video, and then independently segmenting the rest of the frames in that video. However, the model lacks the ability to l...

Iterative Voting

Multiple People Tracking Using Non-iterative Tensor Voting Method

Human tracking is an emerging research field in computer vision and video surveillance. Lightning changes and occlusion are the main challenges faced during tracking. This paper focuses on people tracking both in indoor and outdoor scenes. Our method is based on color modeling using tensor voting framework, which can handle these challenges. The lightning conditions are controlled by homomorphi...