Motion Detection for Video Surveillance

This thesis is related to the broad subject of automatic motion detection and analysis in videosurveillance image sequence. Besides, proposing the new unique solution, some of the previousalgorithms are evaluated, where some of the approaches are noticeably complementary sometimes.In real time surveillance, detecting and tracking multiple objects and monitoring their activities inboth outdoor and indoor environment are challenging task for the video surveillance system. Inpresence of a good number of real time problems limits scope for this work since the beginning. Theproblems are namely, illumination changes, moving background and shadow detection.An improved background subtraction method has been followed by foreground segmentation, dataevaluation, shadow detection in the scene and finally the motion detection method. The algorithm isapplied on to a number of practical problems to observe whether it leads us to the expected solution.Several experiments are done under different challenging problem environment. Test result showsthat under most of the problematic environment, the proposed algorithm shows the better qualityresult.

Motion Cues Analysis for Parkinson Gait Recognition

Background: Previous assessment methods for PG recognition used sensor mechanisms for PG that may cause discomfort. In order to avoid stress of applying wearable sensors, computer vision (CV) based diagnostic systems for PG recognition have been proposed. Main constraints in these methods are the laboratory setup procedures: Novel colored dresses for the patients were specifically designed to segment the test body from a specific colored background. Objective: To develop an image processing tool for home-assessment of Parkinson Gait(PG) by analyzing motion cues extracted during the gait cycles. Methods: The system is based on the idea that a normal body attains equilibrium during the gait by aligning the body posture with the axis of gravity. Due to the rigidity in muscular tone, persons with PD fail to align their bodies with the axis of gravity. The leaned posture of PD patients appears to fall forward. Whereas a normal posture exhibits a constant erect posture throughout the gait. Patients with PD walk with shortened stride angle (less than 15 degrees on average) with high variability in the stride frequency. Whereas a normal gait exhibits a constant stride frequency with an average stride angle of 45 degrees. In order to analyze PG, levodopa-responsive patients and normal controls were videotaped with several gait cycles. First, the test body is segmented in each frame of the gait video based on the pixel contrast from the background to form a silhouette. Next, the center of gravity of this silhouette is calculated. This silhouette is further skeletonized from the video frames to extract the motion cues. Two motion cues were stride frequency based on the cyclic leg motion and the lean frequency based on the angle between the leaned torso tangent and the axis of gravity. The differences in the peaks in stride and lean frequencies between PG and normal gait are calculated using Cosine Similarity measurements. Results: High cosine dissimilarity was observed in the stride and lean frequencies between PG and normal gait. High variations are found in the stride intervals of PG whereas constant stride intervals are found in the normal gait. Conclusions: We propose an algorithm as a source to eliminate laboratory constraints and discomfort during PG analysis. Installing this tool in a home computer with a webcam allows assessment of gait in the home environment.

Pregnancy-related low back pain and pelvic girdle pain approximately 14 months after pregnancy : pain status, self-rated health and family situation

Background: Pelvic girdle pain (PGP) in pregnancy is distinct from pregnancy-related low back pain (PLBP). However, women with combined PLBP and PGP report more serious consequences in terms of health and function. PGP has been estimated to affect about half of pregnant women, where 25% experience serious pain and 8% experience severe disability. To date there are relatively few studies regarding persistent PLBP/PGP postpartum of more than 3 months, thus the main objective was to identify the prevalence of persistent PLBP and PGP as well as the differences over time in regard to pain status, self-rated health (SRH) and family situation at 12 months postpartum. Methods: The study is a 12 month follow-up of a cohort of pregnant women developing PLBP and PGP during pregnancy, and who experienced persistent pain at 6 month follow-up after pregnancy. Women reporting PLBP/PGP (n = 639) during pregnancy were followed up with a second questionnaire at approximately six month after delivery. Women reporting recurrent or persistent LBP/PGP at the second questionnaire (n = 200) were sent a third questionnaire at 12 month postpartum. Results: A total of 176 women responded to the questionnaire. Thirty-four women (19.3%) reported remission of LBP/PGP, whereas 65.3% (n = 115) and 15.3% (n = 27), reported recurrent LBP/PGP or continuous LBP/PGP, respectively. The time between base line and the 12 months follow-up was in actuality 14 months. Women with previous LBP before pregnancy had an increased odds ratio (OR) of reporting 'recurrent pain' (OR = 2.47) or 'continuous pain' (OR = 3.35) postpartum compared to women who reported 'no pain' at the follow-up. Women with 'continuous pain' reported statistically significant higher level of pain at all measure points (0, 6 and 12 months postpartum). Non-responders were found to report a statistically significant less positive scoring regarding relationship satisfaction compared to responders. Conclusions: The results from this study demonstrate that persistent PLBP/PGP is a major individual and public health issue among women 14 months postpartum, negatively affecting their self-reported health. However, the perceived relationship satisfaction seems to be stable between the groups.

Struggling with daily life and enduring pain : a qualitative study of women's experiences with pelvic girdle pain during pregnancy

Background. Few studies have investigated the experiences of living with pelvic girdle pain (PGP) and its impact on pregnant women’s lives. To address this gap in knowledge, this study investigates the experiences of women living with PGP during pregnancy. Methods. A purposive sample, of nine pregnant women with diagnosed PGP, were interviewed about their experiences. Interviews were recorded, transcribed to text and analysed using a Grounded Theory approach. Results. The core category that evolved from the analysis of experiences of living with PGP in pregnancy was “struggling with daily life and enduring pain”. Three properties addressing the actions caused by PGP were identified: i) grasping the incomprehensible; ii) balancing support and dependence and iii) managing the losses. These experiences expressed by the informants constitute a basis for the consequences of PGP: iv) enduring pain; v) being a burden; vi) calculating the risks and the experiences of the informants as vii) abdicating as a mother. Finally, the informants’ experiences of the consequences regarding the current pregnancy and any potential future pregnancies is presented in viii) paying the price and reconsidering the future. A conceptual model of the actions and consequences experienced by the pregnant informants living with PGP is presented. Conclusions. PGP during pregnancy greatly affects the informant’s experiences of her pregnancy, her roles in relationships, and her social context. For informants with young children, PGP negatively affects the role of being a mother, a situation that further strains the experience. As the constant pain disturbs most aspects of the lives of the informants, improvements in the treatment of PGP is of importance as to increase the quality of life. This pregnancy-related condition is prevalent and must be considered a major public health concern during pregnancy.

Motion cue analysis for parkinsonian gait recognition

This paper presents a computer-vision based marker-free method for gait-impairment detection in Patients with Parkinson's disease (PWP). The system is based upon the idea that a normal human body attains equilibrium during the gait by aligning the body posture with Axis-of-Gravity (AOG) using feet as the base of support. In contrast, PWP appear to be falling forward as they are less-able to align their body with AOG due to rigid muscular tone. A normal gait exhibits periodic stride-cycles with stride-angle around 45o between the legs, whereas PWP walk with shortened stride-angle with high variability between the stride-cycles. In order to analyze Parkinsonian-gait (PG), subjects were videotaped with several gait-cycles. The subject's body was segmented using a color-segmentation method to form a silhouette. The silhouette was skeletonized for motion cues extraction. The motion cues analyzed were stride-cycles (based on the cyclic leg motion of skeleton) and posture lean (based on the angle between leaned torso of skeleton and AOG). Cosine similarity between an imaginary perfect gait pattern and the subject gait patterns produced 100% recognition rate of PG for 4 normal-controls and 3 PWP. Results suggested that the method is a promising tool to be used for PG assessment in home-environment.