Dieter Niederkorn

Compression of 2D and 3D navigation video sequences using skip mode masking of static areas

In order to assert correct behavior of electronics in modern automobiles, extensive tests are conducted. Part of these tests focus on the correct rendering of the navigation systems, including map rotation, content of info boxes and smoothness of frame updates. Test engineers have the need to record the rendered navigation system in live setups (e.g. in moving cars) and evaluate them afterwards. Traditional video encoding produces significant bitrate overhead due to the rotating characteristics of the navigation since rotation is approximated with small macroblock partitioning. In this paper, we show how to construct an encoding scheme specifically designed for encoding of 2D and 3D navigation video sequences. For this purpose we develop a Global Motion Estimation (GME) based on feature matching and model parameter estimation and combine it with an H.264/AVC video encoder as backend. By using skip mode information from the H.264/AVC rate distortion optimization, we are able to stabilize the parameter estimation process even in the presence of large static areas.

Robust Rotational Motion Estimation for efficient HEVC compression of 2D and 3D navigation video sequences

In the context of test automation for automobiles, the compressed video recording of infotainment system components like navigation devices is a required practice. These recordings are then analyzed, archived, and forwarded to the responsible engineering teams. In order to compress navigation video sequences efficiently, the dominant rotational motion must be compensated properly. However, the process of Rotational Motion Estimation (RME) is hindered by the presence of static areas like info boxes and overlay graphics. We analyze this problem and show how to build masks for static areas in order to allow high speed feature transforms to be applied. With the acquired fast and accurate RME, we then demonstrate how to significantly reduce the required bitrate during HEVC encoding of navigation sequences.

Blind frame freeze detection in coded videos

In multimedia systems, system errors and artifacts should be avoided in order to keep the Quality of Experience (QoE) of the user as high as possible. For that, the system should be tested and monitored for a long time to assure normal operation. In this paper, we present a new algorithm that automatically detects freezing artifacts in coded videos. The system output is captured and encoded, and the error/artifact detection is run later on the decoded video. One major constraint on our detection algorithm is that every freeze should be detected in order to analyze the reason of its occurrence. Such a constraint entails a high number of false alarms when using the standard freeze detection algorithms. For that, we present a new algorithm that keeps the number of true positives to its maximum, while minimizing the number of false positives.

Freeze detection in 2D navigation video sequences by matching of extracted line segments

In this paper, we present an automated error/ artifact detection framework that monitors the infotainment system of the car. Specifically, this paper focuses on the detection of freezing artifacts that could occur in the navigation system of the car during field tests. Knowing that the motion in the navigation system could also stop when the car stops, it is crucial to differentiate between this situation and a real freezing artifact. We propose an algorithm that reliably detects map jumps which occur after the freezing artifacts. The proposed algorithm extracts lines from the possibly frozen frame and the frame following the freeze event and matches the extracted lines together in order to output a geometric transformation matrix that describes the motion between both frames. If the motion is larger than normal, a map jump is detected and a freeze event is signaled.

Novel Similarity-Invariant Line Descriptor and Matching Algorithm for Global Motion Estimation

We present a new and fast line descriptor and matching algorithm to geometrically register video frames that are deformed by a similarity transformation and contain line segments but with very low texture details, such as navigation maps. Line segments are extracted from the frames, and each line is described with a novel line descriptor that does not depend on pixel intensities. The described lines are then matched together and the matches are input to an outlier removal algorithm in order to estimate the parameters of the transformation describing the global motion between the frames. We propose a method for fast parameter estimation of the transformation using line segments instead of points. Additionally, we apply this algorithm in the testing and error detection context of navigation systems, in which we show how to detect map jump artifacts that could occur during the development of these systems, leading to a jerky and unsmooth motion between the frames. The proposed descriptor and its matching algorithm are shown to be fast enough for online use and very robust against a wide range of translation, rotation, and scale changes. Furthermore, the error detection algorithm allows to detect almost all map jump artifacts while maintaining a very low number of false alarms.

Motion vector analysis based homography estimation for efficient HEVC compression of 2D and 3D navigation video sequences

Navigation systems have become complex devices in automobiles nowadays. As part of large in-car infotainment systems, these devices undergo extensive hardware and software tests in order to assert correct system behavior under all circumstances. During field tests, the display output is typically recorded in compressed form for days or weeks, followed by a thorough analysis of the video data. In this paper, we demonstrate how to setup an HEVC-based compression solution specifically designed for navigation sequence content. We show how rotational motion, which is a dominant characteristic, can be estimated and compensated in an efficient way. We avoid any complex feature-based approaches for global motion estimation but find precise motion parameters by analyzing and filtering motion vector sets produced by HEVC during encoding. While achieving compression efficiency similar to a feature-based approach, processing time for global motion estimation can be significantly reduced.

A novel similarity-invariant line descriptor for geometric map registration

In this paper we present a new line descriptor that can be used in the process of tracking 2D navigation maps that are low in texture details. The problem of tracking this kind of maps is very important in the development and testing phases of a navigation system. In order to track the motion of the map, which could be a translation, rotation, or scale (also known as similarity transform), line segments are used as features and are matched between two consecutive frames using the proposed descriptor in order to determine the motion between the frames. The descriptor is shown to be very robust against typical translation, rotation, and scale transformations, while requiring an acceptable processing time.

Freeze detection in 2D navigation video sequences overlaid with real satellite images

This paper focuses on the detection of freezing artifacts that could occur in the navigation system of the car during field tests. Knowing that the motion in the navigation system could also stop when the car stops, it is crucial to differentiate between this situation and a real freezing artifact. We propose an algorithm that reliably detects map jumps which occur after the freezing artifacts. The proposed algorithm extracts invariant features from the possibly frozen frame and the frame following the freeze event and matches the features in order to output a geometric transformation that describes the motion between both frames. If the motion is larger than normal, a map jump is detected and a freeze event is signaled.

Spiral search based fast rotation estimation for efficient HEVC compression of navigation video sequences

During the development and testing of navigation systems for modern cars, the video streams of the systems-under-test are carefully observed for errors of any kind. While this observation is typically carried out manually by software engineers monitoring the video output, the complexity and variety of the latest navigation systems demand an automated analysis of system functionality. Recently published work on automated error detection for navigation systems [1] can only enfold its full functionality if video sequences can be recorded and compressed in real-time, so that the full test program can be run under lab conditions after recording. However, the rotational motion of these sequences makes efficient compression a difficult task. In this paper, we present a fast and efficient method for rotation estimation, so that rotational motion compensation and thus efficient encoding can take place. Compared to existing state of the art approaches for SIFT- or SURF-based global motion estimation, our scheme requires 1/16th of the original processing time while providing almost identical quality gains of up to 2.5dB.

Compression of 2D navigation sequences with rotational and translational motion

In-car navigation systems have grown in complexity over the recent years, most notably in terms of route calculation, usability and graphical rendering. In order to guarantee correct system behavior, navigation systems need to be tested under real operating conditions, i.e. with field-tests on the road. In this paper, we will focus on a fast compression solution for 2D navigation renderings, so that field-tests can be archived and handed over to software engineers for subsequent evaluation. No parameters from the rendering procedure are available since access to the system is limited to the raw display signal. Rotation is a dominant factor throughout all navigation sequences, so we show how to reconstruct rotational motion parameters with high accuracy and develop a Global Motion Estimation (GME) method as support for a subsequent H.264/AVC video encoder. By integrating ratedistortion optimization concepts into our scheme, we can efficiently omit the segmentation of static and non-static areas. The runtime of the compression solution, which achieves bitrate savings of up to 19.5%, is evaluated both on a laptop CPU and an embedded OMAP4430 system on chip.