Description:
We present a computationally efficient RGB-D based pose estimation solution for less computationally resourced MAVs, which are ideally suited as members in a swarm. Our approach applies the sufficient statistics derived for a least-squares problem to our problem context. RANSAC-based outlier detection in aligning corresponding feature points is a time consuming operation in visual pose estimation. The additive nature of the used sufficient statistics significantly reduces the computation time of the RANSAC procedure since the pose estimation in each test loop can be computed by reusing previously computed sufficient statistics. This eliminates the need for recomputing estimates from scratch each time. A simpler hypotheses testing method gave similar performance in terms of speed but less accurate than our proposed method. We further increase the efficiency by reducing the problem size to four dimensions using attitude data from an Attitude and Heading Reference System (AHRS). Using a real-world dataset, we show that our algorithm saves up to 94% of computation time for the RANSAC-based procedure in pose estimation while improving the accuracy.
Description:
Enhancing the current services or deploying new services operating in RF spectrum requires more licensed spectrum which may not be provided by the regulatory bodies because of spectrum scarcity. On the contrary, recent studies suggest that many portions of the licensed spectrum remains unused or underused for significant period of time raising the issue of spectrum access without license in an opportunistic manner. Among all the spectrum accessing techniques, sensing based methods are considered optimal for their simplicity and cost effectiveness. In this paper, we introduce a new cooperative spectrum sensing technique which considers the spatial variation of secondary (unlicensed) users and each user's contribution is weighted by a factor that depends on received power and path loss. Compared to existing techniques, the proposed one increases the sensing ability and spectrum utilization, and offers greater robustness to noise uncertainty. Moreover, this cooperative technique uses very simple energy detector as its building block thereby reduces the cost and operational complexity.
Description:
Enhancing the current services or deploying new services operating in RF spectrum requires more licensed spectrum which may not be provided by the regulatory bodies because of spectrum scarcity. On the contrary, recent studies suggest that many portions of the licensed spectrum remains unused or underused for significant period of time raising the issue of spectrum access without license in an opportunistic manner. Among all the spectrum accessing techniques, sensing based methods are considered optimal for their simplicity and cost effectiveness. In this paper, we introduce a new cooperative spectrum sensing technique which considers the spatial variation of secondary (unlicensed) users and each user's contribution is weighted by a factor that depends on received power and path loss. Compared to existing techniques, the proposed one increases the sensing ability and spectrum utilization, and offers greater robustness to noise uncertainty. Moreover, this cooperative technique uses very simple energy detector as its building block thereby reduces the cost and operational complexity.
Description:
Protection of interference on the primary system is the key requirement for deployment of a cognitive radio system. Typically, spectrum sensing is interleaved in the transmission process of a secondary user to detect the return of primary user for quick evacuation, resulting in frequent stopping of transmission. In this paper, we introduce a novel method of agile spectrum evacuation that ensures continuous transmission by the secondary user until the primary user actually returns. The sensing process goes on simultaneously by a dedicated set of users working in a cooperative manner. The proposed method is evaluated under fading and shadowing conditions and better interference protection and improved utilization of RF spectrum is obtained.
Description:
One of the most important aspects of cognitive radio technology is to avoid interference on the primary system. Typically, the interference is avoided by sensing a particular spectrum band for the existence of primary transmitter while all secondary users are kept quiet. Hence, a periodic sensing method is used which incorporates alternate phases of sensing and transmission by all secondary users. In this paper, we introduce a new method of agile spectrum evacuation that allows any secondary user to continue using the band until the return of the primary user is detected through the formation of a set of users that exclusively engages in sensing primary user in a cooperative manner. The proposed method yields better interference protection and enhanced spectrum utilization.
Description:
Fixed spectrum licensing policies are unsuitable to meet RF spectrum demand by emerging technologies. Spectrum scarcity is hindering the enhancement of current services or deployment of new services operating in RF spectrum. On the contrary, many portions of the licensed spectrum remain unused or underused for significant period of time creating possibility of opportunistic spectrum access without license. Spectrum sensing is practiced in most of the existing opportunistic spectrum access methods. However, these methods consider identical fading or shadowing channels and ignore spatial variation of unlicensed users, hence fail to capture realistic scenario. We introduce an improved cooperative spectrum sensing technique which incorporates non-identical fading and shadowing, and weighs each non-licensee user's contribution appropriately considering the received power and positional displacements of the users. The proposed method demonstrates better detection accuracy and higher spectrum utilization with fewer cooperating users than other existing methods.
Description:
One of the most challenging issues in cognitive radio networks is to dynamically access the radio frequency spectrum in an uninterrupted manner. To achieve this, omniscient allocation of spectrum bands among cognitive radio users is crucial. Most of the existing spectrum allocation methods select a band from a pool according to the service requirements of a single user, neglecting the demand of multiple users. In this paper, we introduce a collaborative framework for allocating multiple bands among multiple secondary users. The proposed method defines a capacity of service metric based on the optimal sensing parameters and utilizes this metric to assign distinct bands to all or highest possible number of contending users. Performance evaluation suggests that the proposed method exhibits significant superiority over conventional approaches in terms of improved throughput and spectrum utilization, reduced interference loss and collision, and hence, enhances dynamic spectrum access and sharing capabilities.
Description:
Spatial analysis of salient feature points has been shown to be promising in image analysis and classification. In the past, spatial pyramid matching makes use of both of salient feature points and spatial multiresolution blocks to match between images. However, it is shown that different images or blocks can still have similar features using spatial pyramid matching. The analysis and matching will be more accurate in scale space. In this paper, we propose to do spatial pyramid matching in scale space. Specifically, pyramid match histograms are computed in multiple scales to refine the kernel for support vector machine classification. We show that the combination of salient point features, scale space and spatial pyramid matching improves the original spatial pyramid matching significantly.
Description:
Motion vectors of depth-maps in multiview and free-viewpoint videos exhibit strong spatial as well as inter-component clustering tendency. This paper presents a novel motion vector coding technique that first compresses the multidimensional bitmaps of macro block mode information and then encodes only the non-zero components of motion vectors. The bitmaps are partitioned into disjoint cuboids using binary tree based decomposition so that the 0's and 1's are either highly polarized or further sub-partitioning is unlikely to achieve any compression. Each cuboid is entropy-coded as a unit using binary arithmetic coding. This technique is capable of exploiting the spatial and inter-component correlations efficiently without the restriction of scanning the bitmap in any specific linear order as needed by run-length coding. As encoding of non-zero component values no longer requires denoting the zero value, further compression efficiency is achieved. Experimental results on standard multiview test video sequences have comprehensively demonstrated the superiority of the proposed technique, achieving overall coding gain against the state-of-the-art in the range [17%,51%] and on average 31%.