Evaluation of tone mapping and exposure fusion algorithms on HDR videos for face detection and recognition

Download

METU_Thesis_2339372.pdf

Date

2022-2-08

Author

Çavdarlı, Fehime Betül

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

200
views

147
downloads

High dynamic range (HDR) images have become popular recently especially for video surveillance systems. One of the most important reasons for this is that in areas where there is under or over-exposure, classical low dynamic range (LDR) images are insufficient to capture details, while HDR images have better visual details and contain wide range illumination values. However, since HDR images cannot be viewed on conventional LDR displays, additional processing such as tonemapping and/or fusion are required to convert HDR images to LDR images without losing the details. In this thesis, sequential video frames with 3 different exposure times are obtained with an HDR-capable camera. After HDR images are obtained from these images they are deghosted using a state-of-the-art deghosting algorithm to minimize visual artifacts due to object motion. Then 34 different tone mapping operators (TMO) and 20 different exposure fusion algorithms (EFA) have been applied to deghosted video frames. The face detection performance of these algorithms is evaluated by calculating mAP and the performance in terms of face recognition is evaluated by calculating precision, recall, and F1-score with different averaging methods. The results suggest that images obtained with HDR imaging algorithms improve face detection and, in particular, face recognition results, however there are noticeable differences between the performances of different algorithms. As such our study sheds light on which HDR algorithms are more suitable for using in a video surveillance scenario if the goal is to improve the performance of face detection and recognition. We also make available a public dataset as well as a labeling software to stimulate further research in this direction.

Subject Keywords

High dynamic range imaging, Tone mapping, Exposure fusion, Face detection, Face recognition

URI

https://hdl.handle.net/11511/96680

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

Privacy protection of tone-mapped HDR images using false colours ÇİFTÇİ, Serdar; Akyüz, Ahmet Oğuz; PİNHEİRO, Antonio M. G.; Ebrahimi, Touradj (2017-12-01) High dynamic range (HDR) imaging has been developed for improved visual representation by capturing a wide range of luminance values. Owing to its properties, HDR content might lead to a larger privacy intrusion, requiring new methods for privacy protection. Previously, false colours were proved to be effective for assuring privacy protection for low dynamic range (LDR) images. In this work, the reliability of false colours when used for privacy protection of HDR images represented by tone-mapping operators...
Automatic saturation correction for dynamic range management algorithms Artusi, Alessandro; POULİ, Tania; BANTERLE, Francesco; Akyüz, Ahmet Oğuz (2018-04-01) High dynamic range (HDR) images require tone reproduction to match the range of values to the capabilities of a display. For computational reasons and given the absence of fully calibrated imagery, rudimentary color reproduction is often added as a post-processing step rather than integrated into tone reproduction algorithms. In the general case, this currently requires manual parameter tuning, and can be automated only for some global tone reproduction operators by inferring parameters from the tone curve....
Do HDR displays support LDR content? a psychophysical evaluation Akyüz, Ahmet Oğuz; Riecke, Bernhard E.; Reinhard, Erik; Buethoff, Heinrich H. (2007-07-01) The development of high dynamic range (HDR) imagery has brought us to the verge of arguably the largest change in image display technologies since the transition from black-and-white to color television. Novel capture and display hardware will soon enable consumers to enjoy the HDR experience in their own homes. The question remains, however, of what to do with existing images and movies, which are intrinsically low dynamic range (LDR). Can this enormous volume of legacy content also be displayed effectivel...
An evaluation of image reproduction algorithms for high contrast scenes on large and small screen display devices Akyüz, Ahmet Oğuz; Aydın, Murat (2013-11-01) Rendering high contrast scenes on display devices with limited dynamic range is a challenging task. Two groups of algorithms have emerged to take up this challenge: tone mapping operators (TMOs) and more recently exposure fusion (EF) techniques. While several formal evaluation studies comparing TMOs exist, no formal evaluation has yet been performed that compares EF techniques with each other or compares them against TMOs. Moreover, with the advancements in hand-held devices and programmable digital cameras...
An Evaluation of ghost removal algorithms for exposure fusion Kutlu, Tuğser; Akar, Gözde; Department of Electrical and Electronics Engineering (2015) In high dynamic range imaging (HDR), the goal is to capture a scene with a higher dynamic range than the camera capable of capturing with a single exposure. Similar to HDR, exposure fusion is a process that takes multiple images and combines them to create a single dynamically enhanced image by only keeping the properly exposed elements. When using multiple images, local motion of objects can influence the quality of the final image in such a way that local motion of objects causes a ghost artifact. In this...

Citation Formats

F. B. Çavdarlı, “Evaluation of tone mapping and exposure fusion algorithms on HDR videos for face detection and recognition,” M.S. - Master of Science, Middle East Technical University, 2022.