Giwon Kim

Power-rate-distortion modeling for energy minimization of portable video encoding devices

In portable multimedia devices, one of the most critical issues is to minimize the energy consumption and thereby prolong the operational lifetime of the system while maintaining the required video quality. In this paper, we proposed a power-rate-distortion (P-R-D) model of video encoding system to maximize its lifetime. The proposed P-R-D model of video encoder is generated in two steps. The first step is the modeling process of the relationship between the power consumption and the distortion of video encoder. For this, we developed a power consumption model of a video encoder based on a power-scalable architecture of H.264/AVC encoder using the power consumption data of each functional module. The second step is generating the unified P-R-D model based on the P-D model and the conventional rate-distortion (R-D) model. Experimental results show that the proposed P-R-D model describes the relationship among power, rate, and distortion with 0.99 of the R-square value on the average.

Event statistics and criticality-aware bitrate allocation to minimize energy consumption of memory-constrained wireless surveillance system

An event criticality-aware wireless surveillance system tries to minimize the energy consumption by adjusting the image distortion (or quality) requirement according to event criticality. In this paper, we present a novel video encoding method which scales bitrate so as to minimize the energy consumption of the wireless surveillance system while satisfying the given memory constraint. Given event statistics, memory size, and distortion requirement, the presented method gives an energy-optimal bitrate based on an analytic formulation of energy-rate-distortion (E-R-D) relationship for the target system consisting of H.264 video encoder, event detector, transceiver and memory. Experimental results show that the proposed method offers up to 59.6% (29.1% on average) energy savings compared to an existing bitrate allocation method which does not consider event statistics [14].

A low cost single-pass fractional motion estimation architecture using bit clipping for H.264 video codec

As the video resolution increases, high computational complexity of the fractional motion estimation (FME) introduces difficulty to meet real-time constraints in a video coding. In this paper, we proposed a single-pass FME algorithm and its architecture with low hardware cost and negligible loss of the image quality. The proposed algorithm directly searches only surroundings of both the predicted fractional motion vector and the search center. To reduce the hardware cost of processing units in the proposed FME architecture, bit clipping scheme is applied to processing units reducing the hardware cost by 25%. Experimental results show that the proposed algorithm provides almost the same rate-distortion performance as the full-search algorithm. The result of hardware implementation shows that a quad full high definition video (4096×2160) can be processed in real time (24 frame/sec) using 134k gates when the operating frequency is 250MHz. Compared with the recent work supporting quad full high definition video [8], the proposed FME architecture has shown 70% reduction of the hardware cost.

Energy-Aware Operation of Black Box Surveillance Cameras under Event Uncertainty and Memory Constraint

In this paper, we propose an event-driven black box surveillance camera which reduces energy consumption by waking up the system only when an event is detected and dynamically adjusting the video encoding and the resultant image distortion according to the criticality of captured frames called significance level. To achieve this goal, we find an encoding bitrate minimizing the energy consumption of the camera while satisfying the limited memory space constraint and distortion requirement at each significance level by judiciously allocating bit-rate to each significance level. To do that, we considered the trade-off relations between the total energy consumption vs. encoding bit-rate according to the significance level. For further energy savings, we also proposed a low complexity solution which adjusts the energy-minimal encoding bit-rate based on the dynamically changing event behavior, i.e., timing and duration of events. Experimental results show that the proposed method yields up to 67.49% (49.19% on average) energy savings compared to the conventional bitrate allocation methods.

Design of energy-aware video codec-based system

Lifetimes of battery-powered monitoring and surveillance systems are limited by the given battery capacity. This could lead either to a complete loss, or to a significant loss of quality in the recorded image, of events. In this paper, we propose a energy-aware video codec-based system design which exploits event characteristics to minimize the energy consumption through energy-aware architecture exploration. Given event statistics, the proposed energy-aware system design methodology carries out the architecture exploration of a wireless surveillance node (WSN) consisting of image sensor, event detector, video encoder, transceiver and memory. Hierarchical event detection algorithms are utilized for trade-offs between energy consumption and detection accuracy. Even if sophisticated event detection algorithms require high computational complexity, they contribute to reduce the number of false detected events. Based on operational framework of power-rate-distortion relationship analysis, we build an energy-rate-distortion optimization technique which gives an energy-optimal operating point of the video encoder under the given memory constraint. Experimental results show that the proposed method prolongs the lifetime of WSN up to 3.76 times compared to an existing bitrate allocation method which does not consider event statistics and hierarchical event detection.

A Content-Aware Video Encoding Scheme Based on Single-Pass Consistent Quality Control

In real-time video streaming applications based on battery-powered camera systems, it is crucial to capture and transmit critical information satisfying the storage capacity and channel bandwidth requirement. In this paper, we propose a single-pass content-aware video encoding scheme for such applications to achieve a consistent video quality while satisfying the bit-rate constraints. To achieve the objective we developed: 1) scene descriptor based on the discrete cosine transformation coefficients obtained from the video encoder; 2) a parameterized analytic distortion model for video encoding using the scene descriptor; 3) scene change detection based on the encoded MB mode ratio; and 4) a single-pass consistent video quality control scheme which exploits 1), 2), and 3). Experimental results show that the proposed method results in less deviation from the target distortion and less distortion variance than the up-to-date best result by up to 65.25% and 75.88%, respectively, while satisfying the given rate constraints. The computing time overhead in the proposed method was 0.560% and 0.571% for the variable and constrained variable bit-rate mode, respectively, which is negligible in nearly all embedded applications.

Lifetime maximization of video blackbox surveillance camera

In this paper, we propose a lifetime maximization method for battery- and flash-constrained blackbox surveillance node (BSN) consisting of image sensor, event detector, video encoder, flash memory and battery. Because it is not economically feasible to transfer all the recorded images to the base station due to the limited energy in BSN, the recorded images are stored in flash memory for offline event recognition. In BSN, balancing the usage of battery and flash memory is critical to prolong the lifetime, because the shortage of either battery charge or flash capacity could lead to a complete loss of events, or a significant loss of quality in the recorded image of events. The lifetime of BSN is determined by the remaining battery charge and flash memory space. In this work, we assume that the resources of BSN, i.e., battery and flash memory are refreshed every system maintenance period (SMP). The proposed method controls the bit-rate of encoded videos and sampling rate, i.e., resolution and frame rate, to prolong the BSN lifetime till the SMP. Experimental results show that the proposed method prolongs the BSN lifetime by up to 136.36% compared with an existing bit-rate allocation method which does not consider the resource usage balancing.

Lifetime elongation of event-driven wireless video sensor networks

This paper proposes a method to prolong the lifetime of event-driven wireless video sensor networks. The proposed method provides the operating point of each node by firstly selecting the route to the sink node in an energy-aware fashion. Then it finds the lifetime-maximal encoding bit-rate utilizing the event statistics and the analytic power consumption models of major functional blocks in the target video sensor node, i.e., video encoder and wireless transceiver. Furthermore, it additionally controls the encoding frame-rate to balance the lifetime of each node within the selected route when the distribution of event occurrence rate is significantly unbalanced. Experimental results show that the proposed algorithm extends the lifetime of the network by 183.53% on average compared with a conventional bit-rate allocation method.

An energy-aware hierarchical event detection in battery-operated wireless video surveillance systems

In battery-operated wireless video surveillance systems (WVSS), it is mostly required to detect events in an energy-efficient manner due to limited available energy and a huge amount of data to be processed. Therefore, one of the main challenges in the battery-constrained systems is to minimize the energy consumption of the whole system. In this paper, we present an energy-aware event detector which has a hierarchical decision architecture to maximize the system lifetime while achieving the required detection accuracy. An analytical model for the relationship between the complexity of the event detector and system performance is derived based on the given event characteristics. Finally, we suggest a heuristic search algorithm to significantly reduce the heavy computational complexity. Experimental results have shown that the proposed heuristic search algorithm provides 98.17% complexity reduction on average with a negligible deterioration of the system lifetime.

Lifetime maximization of mobile wireless camera system

A mobile wireless camera (MWC) captures scene as it moves around, and then, stores the scene after compression. In this paper, we propose a novel method to extend battery lifetime by intermittently transmitting the compressed data to the base station (BS) through wireless transmission when the distance between MWC and BS is shorter than a given threshold distance; otherwise, compressed data are stored in the internal memory of MWC. We present an analytic method to determine the threshold distance based on the statistics of transmission distance and available memory capacity such that the lifetime of MWC is maximized while preserving all compressed data. Experimental results show that the proposed resource management method offers up to 79.72% (average 33.57%) lifetime improvement compared to the conventional method which transmits encoded data only after memory is full.