Collaborative Camouflaged Object Detection: A Large-Scale Dataset and Benchmark.

In this article, we provide a comprehensive study of a new task called collaborative camouflaged object detection (CoCOD), which aims to simultaneously detect camouflaged objects with the same properties from a group of relevant images. To this end, we meticulously construct the first large-scale dataset, termed CoCOD8K, which consists of 8528 high-quality and elaborately selected images with object mask annotations, covering five superclasses and 70 subclasses. The dataset spans a wide range of natural and artificial camouflage scenes with diverse object appearances and backgrounds, making it a very challenging dataset for CoCOD.

Differential Privacy via Haar Wavelet Transform and Gaussian Mechanism for Range Query.

Range query is the hot topic of the privacy-preserving data publishing. To preserve privacy, the large range query means more accumulate noise will be injected into the input data. This study presents a research on differential privacy for range query via Haar wavelet transform and Gaussian mechanism.

Out-of-plane shape determination in generalized fringe projection profilometry.

The out-of-plane shape determination in a generalized fringe projection profilometry is presented. The proposed technique corrects the problems in existing approaches, and it can cope well with the divergent illumination encountered in the generalized profilometry. In addition, the technique can automatically detect the geometric parameters of the experimental setup, which makes the generalized fringe projection profilometry simple and practical.

Comment on "Fringe projection profilometry with nonparallel illumination: a least-squares approach".

We comment on the recent Letter by Chen and Quan [Opt. Lett.30, 2101 (2005)] in which a least-squares approach was proposed to cope with the nonparallel illumination in fringe projection profilometry.

Class of 4 + 1-phase algorithms with error compensation.

It is well known that phase-shifting interferometry suffers from inaccuracy in the presence of phase-shifting errors. We have proved the limitation of using a 4-phase algorithm to reduce the phase-measurement error in the presence of the phase-shifting error. A class of 4 + 1-phase error compensating algorithms is formulated.