Florian Lang

2papers

2 Papers

HCFeb 15, 2021
Creepy Technology: What Is It and How Do You Measure It?

Paweł W. Woźniak, Jakob Karolus, Florian Lang et al.

Interactive technologies are getting closer to our bodies and permeate the infrastructure of our homes. While such technologies offer many benefits, they can also cause an initial feeling of unease in users. It is important for Human-Computer Interaction to manage first impressions and avoid designing technologies that appear creepy. To that end, we developed the Perceived Creepiness of Technology Scale (PCTS), which measures how creepy a technology appears to a user in an initial encounter with a new artefact. The scale was developed based on past work on creepiness and a set of ten focus groups conducted with users from diverse backgrounds. We followed a structured process of analytically developing and validating the scale. The PCTS is designed to enable designers and researchers to quickly compare interactive technologies and ensure that they do not design technologies that produce initial feelings of creepiness in users.

CVJul 5, 2017
Robust Multi-Image HDR Reconstruction for the Modulo Camera

Florian Lang, Tobias Plötz, Stefan Roth

Photographing scenes with high dynamic range (HDR) poses great challenges to consumer cameras with their limited sensor bit depth. To address this, Zhao et al. recently proposed a novel sensor concept - the modulo camera - which captures the least significant bits of the recorded scene instead of going into saturation. Similar to conventional pipelines, HDR images can be reconstructed from multiple exposures, but significantly fewer images are needed than with a typical saturating sensor. While the concept is appealing, we show that the original reconstruction approach assumes noise-free measurements and quickly breaks down otherwise. To address this, we propose a novel reconstruction algorithm that is robust to image noise and produces significantly fewer artifacts. We theoretically analyze correctness as well as limitations, and show that our approach significantly outperforms the baseline on real data.