## 1 Introduction
Video traces after frame parsing have been examined for two main purposes: the purpose of traffic modeling [39; 40; 41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51; 52; 53; 54; 55] or towards characterization of compressed video by focusing on specific standard [56; 57; 58; 59]. For traffic modeling, studies are related to specific protocols [39], queuing [40], variable bitrates [41], specific prediction models [41; 42; 43; 44; 45; 46; 47; 48; 49; 50; 51], buffering [52], dynamic bandwidth allocation [53], attacks [54] and various content [55]. On the other hand, characterizations of compressed video using specific standard and video traces are considered using MPEG-4 Advanced Simple Profile (ASP) [56], MPEG-4 version 2 and H.263 in [57] and advanced video coding (AVC or H.264) [58] and its extensions in [59]. So far, to the author's knowledge, LRD- and multifractals-based studies oriented towards characterization of compressed video by focusing on specific standard and different compression factors have only been examined up to MPEG-4/AVC content [56; 57; 58; 59], while HEVC should deal with modern HFR video content. Since each standard affects tracing differently, it is crucial to understand the LRD and multifractal behavior of HEVC HFR compressed content while having in mind different compression quality. Moreover, studies related to detection of frame rate upconversions, i.e., temporal resolution recovery (TRR), are presented in [60; 61; 62; 63]. In recent works, MPEG-4 traces have been investigated [60]. They are mostly investigated for original LFR content: frame rates of 24 fps upconverted to 30 fps [61], frame rates of 15 fps [62] and frame rates of 15 to 30 fps [63]. Recent previous studies have shown that it is possible to perform TRR detection [60; 61; 62; 63] using MPEG-4/AVC SFR video content/traces. The purpose of this work is to analyze video traces corresponding to HFR HEVC compressed content using LRD and multifractals and to tackle issue of TRR detection by examining effects found in TRR. Namely, this paper addresses HEVC (or H.265) frame size traces extracted from HFR video content that are considered from an LRD and multifractalpoint of view. As a consequence of the above, the analysis of HFR should go hand in hand with compression observed using constant rate factors. Here, the focus is on UHD HEVC video traces collected from data corresponding to HFR and frequency up to 120 fps, where tests have been performed using publicly available reference HFR video content. Temporal resolution recovery (TRR) has also been examined. The contributions of this paper are as follows:  
* HFR HEVC frame size traces show specific behavior in LRD- and multifractal-based analysis, where difference before and after temporal resolution recovery (TRR) exist. * The experimental results are obtained for HEVC compressed HFR video frame size traces for the first time in multifractal domain, which may contribute to recognition of possible changes like TRR. * Having in mind the obtained results and spectra behavior, a novel detection method is proposed for TRR detection regardless of compression level expressed through constant rate factors. * The proposed TRR detection model based on weighted k-nearest neighbors (weighted kNN or WkNN) classifier shows high accuracy detection percentage in the performed experimental analysis using a relatively low number of features. This paper is organized as follows. After the introduction, in Section 2, a brief description of HFR, video quality and coding is given. In Section 3, additional details on works related to multifractal analysis of compressed video content are presented. Video frame size traces and data gathering are explained in Section 4. Applied methods for LRD and multifractal spectrum calculation are described in Section 5. HFR content is characterized using LRD and multifractal properties before and after TRR. Moreover, novel model for TRR detection is proposed based on HFR video multifractal analysis, WkNN classifier and a relatively low number of multifractal features.